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  • 101.
    Andersson, Sören
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Stoica, Petre
    Polytechnic Institute of Bucharest, Romania.
    Viberg, Mats
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nehorai, Arye
    Yale University, USA.
    Eigenvector Matrix-Beamformers in Array Processing1994Report (Other academic)
  • 102.
    Andersson, Tobias
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Increased Autonomy for Construction Equipment using Laser2010Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    At working sites all around monotonic tasks are performed. If one were able

    to automatize these kinds of tasks there would be a large economical profit to

    collect. Volvo CE are in the process of developing an autonomous wheel loader,

    to perform these types of monotonic, uniform tasks. The project is intended to

    be performed mainly be thesis workers. This report is the eighth thesis in this

    project. Earlier work has made the loader able to see a pile using a laser scanner.

    The machine can also see and fill a hauler. The usage of the laser scanner can

    only be made while the loader is standing still. The aim of this thesis work has

    been to make the loader able to scan its environment while it is moving. To do

    this an inertial measurement unit has been used for keeping track of the scanners

    orientation during a scan. The work of this thesis has resulted in a working set-up

    on the machine, and a robust framework for future work.

     

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    FULLTEXT01
  • 103.
    Andersson, Torbjörn
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Concepts and Algorithms for Non-Linear System Identifiability1994Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Recently, commutative algebra and differential algebra have come to use as mathematical tools for solving problems in automatic control. We will use these tools to answer questions regarding identifiability for models given as a set of differential polynomials. A constructive algorithm, Ritt's algorithm, has been modified for this specific situation. Furthermore, comparisons between Ritt's algorithm and Buchberger's algorithm, to answer the identifiability question when the model structures are given in state space form, are performed. The basic problem is that the computational complexity rapidly increases with the problem size. We examine various ways to simplify the computations in this respect, but it must also be stressed that the complexity increase is inherent in the problem.

    In identification from a deterministic point of view an algorithm is said to be robustly convergent if the true system is regained when the noise level tends to zero. In this thesis we introduce a concept close to this performance measure; robust global identifiability. A model structure, i.e., a smoothly parameterized set of models, is said to be robustly globally identifiable if there exist an identification algorithm such that the true parameters are regained when the noise level tends to zero. In this thesis we show that global identifiability implies robust global identifiability when the considered model structure is a characteristic set of differential polynomials. This means that any model structure with parameters, that can be uniquely estimated from data has this robustness property.

    Finally, a method for estirnation of residence time in continuous flow systems with varying dynamics is discussed. By resampling, i.e., choosing time instants different from the given sampling instants, and interpolation between measured data points, we obtain a continuous fl.ow system with constant residence time expressed in a new resampled time vector. We assume that the fiow patterns in the systems are invariant. The new data set is then used for identification of parameters in a chosen model structure. From the identified model, the residence time is readily calculated and a procedure for that is briefly described. The presented method is readily extended to enable use in recursive identification. In that case the modified recursive identification method is an improvement of the tracking ability compared to an ordinary recursive routine.

  • 104.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of Residence Time in Continuous Flow Systems with Dynamics1994In: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 3, p. 401-406Conference paper (Refereed)
    Abstract [en]

    A method for estimation of residence time in continuous flow systems with varying dynamics is presented. By resampling, i.e., choosing time instants different from the given sampling instants, and interpolation between measured data points, we obtain a continuous flow system with constant residence time expressed in the new resampled time vector. We assume the flow patterns in the systems are invariant. The new data set is then used for identification of parameters in a chosen model structure. From the identified model, the residence time is readily calculated and a procedure for that is briefly described. The presented method is readily extended to enable use in recursive identification. In that case, however, as an improvement of tracking ability of an ordinary recursive routine.

  • 105.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of Residence Time in Continuous Flow Systems with Dynamics1994Report (Other academic)
    Abstract [en]

    A method for estimation of residence time in continuous flow systems with varying dynamics is presented. By resampling, i.e., choosing time instants different from the given sampling instants, and interpolation between measured data points, we obtain a continuous flow system with constant residence time expressed in the new resampled time vector. We assume the flow patterns in the systems are invariant. The new data set is then used for identification of parameters in a chosen model structure. From the identified model, the residence time is readily calculated and a procedure for that is briefly described. The presented method is readily extended to enable use in recursive identification. In that case, however, as an improvement of tracking ability of an ordinary recursive routine.

    Download full text (pdf)
    Estimation of Residence Time in Continuous Flow Systems with Dynamics
  • 106.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of Residence Time in Continuous Flow Systems with Dynamics1994Report (Other academic)
    Abstract [en]

    A method for estimation of residence time in continuous flow systems with varying dynamics is presented. By resampling, i.e., choosing time instants different from the given sampling instants, and interpolation between measured data points, we obtain a continuous flow system with constant residence time expressed in the new resampled time vector. We assume the flow patterns in the systems are invariant. The new data set is then used for identification of parameters in a chosen model structure. From the identified model, the residence time is readily calculated and a procedure for that is briefly described. The presented method is readily extended to enable use in recursive identification. In that case, however, as an improvement of tracking ability of an ordinary recursive routine.

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    Estimation of Residence Time in Continuous Flow Systems with Dynamics
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    FULLTEXT01
  • 107.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of Residence Time in Continuous Flow Systems with Dynamics1995In: Journal of Process Control, ISSN 0959-1524, E-ISSN 1873-2771, Vol. 5, no 1, p. 9-17Article in journal (Refereed)
    Abstract [en]

    A method for estimation of residence time in continuous flow systems with varying dynamics is presented. By resampling, i.e., choosing time instants different from the given sampling instants, and interpolation between measured data points, we obtain a continuous flow system with constant residence time expressed in the new resampled time vector. We assume the flow patterns in the systems are invariant. The new data set is then used for identification of parameters in a chosen model structure. From the identified model, the residence time is readily calculated and a procedure for that is briefly described. The presented method is readily extended to enable use in recursive identification. In that case, however, as an improvement of tracking ability of an ordinary recursive routine. Keywords : System identification, residence time estimation, time-varying systems, variable flow and/or volume, continuous flow systems, recursive identification.

  • 108.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of Residence Time in Continuous Flow Systems with Varying Flow and Volume1993Report (Other academic)
    Abstract [en]

    A method for estimation of residence time in continuous flow vessels with variable flow and volume is presented. By resampling, i.e., choosing time instants different from the given sampling instants, and interpolation of measured data points, we obtain a continuous flow system with constant residence time expressed in the new resampled time vector, assuming the flow patterns in the vessels and tanks are invariant. The new data set is then used for identification of parameters in a chosen model structure. From the identified model the residence time is easily calculated and a procedure for that is briefly described. The presented method is easily extended to enable use in recursive identification but then as an improvement of tracking ability of an ordinary recursive routine.

  • 109.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identifying Models using Piecewise Linear Approximation of Input Signals1992Report (Other academic)
    Abstract [en]

    Very often in system identification problems it is assumed that the input signal is piecewise constant but in many practical cases this is not the fact. In such cases when the input signal is continuous it shows that a piecewise linear approximation of the input signal leads to a better model. In this report it is shown how to handle system identification problems using state space descriptions and the assumption of piecewise linear input signals with MathWork's system identification software.

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  • 110.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Isaksson, Alf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Projekt operatörsverktyg, delprojekt 4: Modeller för massatransport och beräkning av uppehållstid i fiberlinjen. Slutrapport1992Report (Other academic)
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    FULLTEXT01
  • 111.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification Aspects of Inter-Sample Input Behavior1994In: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 3, p. 137-142Conference paper (Refereed)
    Abstract [en]

    In this contribution aspects of inter-sample input signal behavior are examined. The starting point is that parametric identification always is performed on basis of discrete-time data. This is valid for identification of discrete-time models as well as continuous-time models. The usual assumptions on the input signal are; i) it is band-limited, ii) it is piecewise constant or iii) it is piecewise linear. One point made in this paper is that if a discrete-time model is used, the best possible (in the model structure) adjustment to data is made. This is independent of the assumption on the input signal. However, a transformation of the obtained discrete model to a continuous one is not possible without additional assumptions on the input signal. The other point made is that the frequency functions of the discrete models very well coincides with the frequency functions of the discretized continuous time models and the continuous time transfer function fitted in the frequency domain.

  • 112.
    Andersson, Torbjörn
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Pucar, Predrag
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification Aspects of Inter-Sampling Behavior1994Report (Other academic)
    Abstract [en]

    In this contribution aspects of inter-sample input signal behavior are examined. The starting point is that parametric identication always is performed on basis of discrete-time data. This is valid for identication of discrete-time models as well as continuous-time models. The usual assumptions on the input signal are; i) it is band-limited, ii) it is piecewise constant or iii) it is piecewise linear. One point made in this paper is that if a discrete-time model is used, the best possible (in the model structure) adjustment to data is made. This is independent of the assumption on the input signal. However, a transformation of the obtained discrete model to a continuous one is not possible without additional assumptions on the input signal. The other point made is that the frequency functions of the discrete models very well coincides with the frequency functions of the discretized continuous time models and the continuous time transfer function fitted in the frequency domain.

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    fulltext
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    FULLTEXT01
  • 113.
    Andreas, Svensson
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Model Predictive Control with Invariant Sets in Artificial Pancreas for Type 1 Diabetes Mellitus2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis deals with Model Predictive Control (MPC) for artificial pancreas for Type 1 Diabetes Mellitus patients. A control strategy exploiting invariant sets in MPC for blood glucose level control is developed, to the authors knowledge for the first time. The work includes various types of invariant sets relevant for the artificial pancreas problem, and different ways to incorporate them into the MPC strategy. The work is an extension to the zone MPC controller for artificial pancreas developed at University of California Santa Barbara and Sansum Diabetes Research Institute.

    The evaluation of the proposed control strategy is done in silico in the U.S. Food and Drug Administration approved metabolic simulator. The trials show some promising results in terms of more rapid meal responses and decreased variability between the subjects than the zone MPC. An attempt to robust control employing invariant sets proved to be less promising in the evaluations. The results indicate that the direct application of known robust control techniques is not appropriate, and that more appropriate robust control techniques must be searched for, or developed, more specific to the artificial pancreas control.

    Altogether, this thesis pinpoints a possible future direction of artificial pancreas control design, with MPC based on invariant sets.

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    AndreasSvensson_ModelPredictiveControlwithInvariantSetsinArtificialPancreasforType1DiabetesMellitus
  • 114.
    André, Simon
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Design and Optimization of Controllers for an Electro-Hydraulic System2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Electro-Hydraulic (EH) systems are commonly used in the industry for applications that require high power-weight ratios and large driving forces. The EH system studied in this master thesis have recently been upgraded with new hardware components and as a part of this upgrade a new controller was requested. The system consists of a controller that computes a control signal for an electric motor. The motor drives a gear pump that generates a flow of hydraulic fluid. The flow is then directed to a cylinder. The movements of a piston in the cylinder is affected by the flow and the piston position can be measured. The measured piston position is then fed back to the controller and the control loop is complete. The system was previously controlled using a Proportional-Integral-Derivative (PID) controller and the purpose of this thesis is to compare the old controller with alternative control strategies suitable for this application. The evaluation of the controllers is based on both software and hardware simulations and results in a recommendation for final implementation of the best suited controller. The control strategies chosen for investigation are: a retuned PID controller, a PID controller with feed forward from reference, a PID based cascade controller, a Linear Quadratic (LQ) controller, and a Model Predictive Controller (MPC). To synthesize the controllers an approximate model of the system is formed and implemented in the software environment Matlab Simulink. The model is tuned to fit recorded data and provides a decent estimation of the actual system. The proposed control strategies are then simulated and evaluated in Simulink with the model posing as the real system. These simulations resulted in the elimination of the cascade controller as a possible candidate since it proved unstable for large steps in the reference signal. The remaining four controllers were all selected for simulation on the real hardware system. Unfortunately the MPC was never successfully implemented on the hardware due to some unknown compatibility error and hence eliminated as a possible candidate. The three remaining control strategies, PID, PID with feed forward from reference and the LQ controller, were all successfully implemented and simulated on hardware. The results from the hardware simulations compared to simulations made with the old controller, as well as the results from the software simulations, were then evaluated. Depending on the purpose one of two control strategies is recommended for this application. The LQ controller achieved the best overall performance and is presented as the control strategy best suited for this application.

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    Master_Thesis_SA_2014
  • 115.
    Andrén, Filip
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Optimization of Random Access in 3G Long Term Evolution2009Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Before a mobile can commence services it needs to have access to a base station. The access method is often referred to as random access (RA). One way to measure the performance of the RA procedure is the access delay (AD) of the mobiles, where AD is the time from which a mobile wants to start a RA attempt until it has received access.

    There are different approaches to optimize the RA procedure. Manual optimization is possible but costly. Automated optimization is preferable because of the lower costs and the possibility to change configuration fast in the base station when the operational conditions change. This thesis focuses on automated optimization of the RA procedure with regard to AD.

    A controllability and observability study of AD is first presented in this thesis. The controllability study shows that AD can be controlled by a number of RA parameters, whereas the observability study show that AD cannot always be correctly observed. The next part of this thesis presents a controller synthesis, where three different controllers are presented to control a specified percentile of AD. It is shown, through experiments, that the controllers derived can be used to optimize the RA procedure with regard to AD.

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  • 116.
    Ankelhed, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    An Efficient Implementation of Gradient and Hessian Calculations of the Coefficients of the Characteristic Polynomial of I-XY2011Report (Other academic)
    Abstract [en]

    This is a report about a project in robust multivariable control. In the project we investigated how to decrease the computational complexity of calculating the gradient and Hessian of coefficients of the characteristic polynomial of the matrix I-XY that often appear in H-infinity controller synthesis. Compared to a straight-forward implementation, our new implementation managed to decrease the number of operations required to calculated the gradient and Hessian by several orders of magnitude by utilizing the structure of the problem.

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  • 117. Order onlineBuy this publication >>
    Ankelhed, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On design of low order H-infinity controllers2011Doctoral thesis, monograph (Other academic)
    Abstract [en]

    When designing controllers with robust performance and stabilization requirements, H-infinity synthesis is a common tool to use. These controllers are often obtained by solving mathematical optimization problems. The controllers that result from these algorithms are typically of very high order, which complicates implementation. Low order controllers are usually desired, since they are considered more reliable than high order controllers. However, if a constraint on the maximum order of the controller is set that is lower than the order of the so-called augmented system, the optimization problem becomes nonconvex and it is relatively difficult to solve. This is true even when the order of the augmented system is low.

    In this thesis, optimization methods for solving these problems are considered. In contrast to other methods in the literature, the approach used in this thesis is based on formulating the constraint on the maximum order of the controller as a rational function in an equality constraint. Three methods are then suggested for solving this smooth nonconvex optimization problem.

    The first two methods use the fact that the rational function is nonnegative. The problem is then reformulated as an optimization problem where the rational function is to be minimized over a convex set defined by linear matrix inequalities (LMIs). This problem is then solved using two different interior point methods.

    In the third method the problem is solved by using a partially augmented Lagrangian formulation where the equality constraint is relaxed and incorporated into the objective function, but where the LMIs are kept as constraints. Again, the feasible set is convex and the objective function is nonconvex.

    The proposed methods are evaluated and compared with two well-known methods from the literature. The results indicate that the first two suggested methods perform well especially when the number of states in the augmented system is less than 10 and 20, respectively. The third method has comparable performance with two methods from literature when the number of states in the augmented system is less than 25.

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    On design of low order H-infinity controllers
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    COVER01
  • 118. Order onlineBuy this publication >>
    Ankelhed, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On low order controller synthesis using rational constraints2009Licentiate thesis, monograph (Other academic)
    Abstract [en]

    In order to design robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the plant, the problem is no longer convex and it is then relatively hard to solve. These problems become very complex, even when the order of the system to be controlled is low.

    The approach used in the thesis is based on formulating the constraint on the maximum order of the plant as a polynomial equation. By using the fact that the polynomial is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex polynomial function is to be minimized over a convex set defined by linear matrix inequalities.

    To solve this optimization problem, two methods have been proposed. The first method is a barrier method and the second one is a method based on a primal-dual framework. These methods have been evaluated on several problems and compared with a well-known method found in the literature. To motivate this choice of method, we have made a brief survey of available methods available for solving the same or related problems.

    The proposed methods emerged as the best methods among the three for finding lower order controllers with the same or similar performance as the full order controller. When the aim is to find the lowest order controller with no worse than +50% increase in the closed loop H-infinity norm, then the three compared methods perform equally well.

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    On low order controller synthesis
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    Cover
  • 119.
    Ankelhed, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Utvärdering av DC-labben2006Report (Other academic)
    Abstract [en]

    I denna rapport jämförs två olika metoder för att ta fram en modell för att kunna reglera en DC-motor med lead-lagreglering. I den ena metoden identifieras två parametrar i en given modell av andra ordningen, medan i den andra metoden skattas ett antal punkter i ett bodediagram direkt med hjälp av frekvensanalys. Resultaten indikerar att de två metoderna är ungefär likvärdiga för den process som studerats.

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    FULLTEXT01
  • 120.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Partially Augmented Lagrangian Method for Low Order H-Infinity Controller Synthesis Using Rational Constraints2011Report (Other academic)
    Abstract [en]

    When designing robust controllers, H-infinity synthesis is a common tool touse. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the (augmented) system, the problem becomes nonconvex and it is relatively hard to solve. These problems become very complex, even when the order of the system is low.

    The approach used in this work is based on formulating the constraint onthe maximum order of the controller as a polynomial (or rational) equation.This equality constraint is added to the optimization problem of minimizingan upper bound on the H-innity norm of the closed loop system subjectto linear matrix inequality (LMI) constraints. The problem is then solvedby reformulating it as a partially augmented Lagrangian problem where theequality constraint is put into the objective function, but where the LMIsare kept as constraints.

    The proposed method is evaluated together with two well-known methodsfrom the literature. The results indicate that the proposed method hascomparable performance in most cases, especially if the synthesized con-troller has many parameters, which is the case if the system to be controlledhas many input and output signals.

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    A partially augmented Lagrangian method for low order H-infinity controller synthesis using rational constraints
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    FULLTEXT03
  • 121.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Partially Augmented Lagrangian Method for Low Order H-Infinity Controller Synthesis Using Rational Constraints2012In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 57, no 11, p. 2901-2905Article in journal (Refereed)
    Abstract [en]

    This technical note proposes a method for low order H-infinity synthesis where the constraint on the order of the controller is formulated as a rational equation. The resulting nonconvex optimization problem is then solved by applying a partially augmented Lagrangian method. The proposed method is evaluated together with two well-known methods from the literature. The results indicate that the proposed method has comparable performance and speed.

  • 122.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Primal-Dual Method for Low Order H-Infinity Controller Synthesis2010In: Proceedings of Reglermöte 2010, Lund, 2010Conference paper (Other academic)
    Abstract [en]

    When designing robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the (augmented) system, the problem becomes nonconvex and it is relatively hard to solve. These problems become very complex, even when the order of the system is low.

    The approach used in this work is based on formulating the constraint on the maximum order of the controller as a polynomial (or rational) equation. By using the fact that the polynomial (or rational) is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex function is to be minimized over a convex set defined by linear matrix inequalities.

    The proposed method is evaluated together with a well-known method from the literature. The results indicate that the proposed method performs slightly better.

  • 123.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Primal-Dual Method for Low Order H-Infinity Controller Synthesis2010Report (Other academic)
    Abstract [en]

    When designing robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the (augmented) system, the problem becomes nonconvex and it is relatively hard to solve. These problems become very complex, even when the order of the system is low.

    The approach used in this work is based on formulating the constraint on the maximum order of the controller as a polynomial (or rational) equation. By using the fact that the polynomial (or rational) is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex function is to be minimized over a convex set defined by linear matrix inequalities.

    The proposed method is evaluated together with a well-known method from the literature. The results indicate that the proposed method performs slightly better.

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  • 124.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Primal-Dual Method for Low Order H-Infinity Controller Synthesis2009In: Proceedings of the 48th IEEE Conference on Decision and Control held jointly with the 28th Chinese Control Conference, IEEE , 2009, p. 6674-6679Conference paper (Refereed)
    Abstract [en]

    When designing robust controllers, H-infinity synthesisis a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the (augmented) system, the problem becomes nonconvex and it is relatively hard to solve. These problems become very complex,even when the order of the system is low.

    The approach used in this work is based on formulating the constraint on the maximum order of the controller as a polynomial (or rational) equation. By using the fact that the polynomial (or rational) is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex function is to be minimized over a convex set defined by linear matrix inequalities.

    The proposed method is evaluated together with a wellknown method from the literature. The results indicate that the proposed method performs slightly better.

  • 125.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Quasi-Newton Interior Point Method for Low Order H-Infinity Controller Synthesis2011In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 56, no 6, p. 1462-1467Article in journal (Refereed)
    Abstract [en]

    This technical note proposes a method for low order H-infinity synthesis where the constraint on the order of the controller is formulated as a rational equation. The resulting nonconvex optimization problem is then solved by applying a quasi-Newton primal-dual interior point method. The proposed method is evaluated together with a well-known method from the literature. The results indicate that the proposed method has comparable performance and speed.

    Download full text (pdf)
    fulltext
  • 126.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Additional Numerical Results for the Quasi-Newton Interior Point Method for Low Order H-Infinity Controller Synthesis2010Report (Other academic)
    Abstract [en]

    Here we present numerical results and timings obtained using our quasi-Newton interior point method on a set of 44 systems. We were not able to include these results in the article due to limited amount of space. Also results from our evaluation of HIFOO on the same systems are included.

    Download full text (pdf)
    FULLTEXT01
  • 127.
    Ankelhed, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Helmersson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Suboptimal Model Reduction using LMIs with Convex Constraints2006Report (Other academic)
    Abstract [en]

    An approach to model reduction of LTI systems using Linear Matrix Inequalities (LMIs) in an H-infinity framework is presented, where non-convex constraints are replaced with stricter convex constraints thus making it suboptimal. The presented algorithms are compared with the Optimal Hankel reduction algorithm, and are shown to achieve better results (i.elower H-infinity errors) in cases where some of the Hankel singular values are close, but not equal to each other.

    Download full text (pdf)
    FULLTEXT01
  • 128.
    Annergren, Mariette
    et al.
    KTH Royal Institute of Technology.
    Khoshfetrat Pakazad, Sina
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Wahlberg, Bo
    KTH Royal Institute of Technology.
    A Distributed Primal-dual Interior-point Method for Loosely Coupled Problems Using ADMMManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper we propose an efficient distributed algorithm for solving loosely coupled convex optimization problems. The algorithm is based on a primal-dual interior-point method in which we use the alternating direction method of multipliers (ADMM) to compute the primal-dual directions at each iteration of the method. This enables us to join the exceptional convergence properties of primal-dual interior-point methods with the remarkable parallelizability of ADMM. The resulting algorithm has superior computational properties with respect to ADMM directly applied to our problem. The amount of computations that needs to be conducted by each computing agent is far less. In particular, the updates for all variables can be expressed in closed form, irrespective of the type of optimization problem. The most expensive computational burden of the algorithm occur in the updates of the primal variables and can be precomputed in each iteration of the interior-point method. We verify and compare our method to ADMM in numerical experiments.

  • 129.
    Antonsson, Jacob
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Motion Tracking Using a Permanent Magnet2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this project the possibility of using a network of magnetometers sensing a permanent magnet for tracking has been investigated. Both the orientation and the position of the magnet have been considered. A dipole approximation of the magnetic field is used to develop two models. One of the models parametrizes the orientation with the magnetic moment vector, while the other parametrizes the orientation with a unit quaternion. An extended Kalman filter have been used to estimate position and orientation.

    Several calibration algorithms have been developed to calibrate for sensor errors, differences in sensor coordinate frame orientations and also for the estimation of the magnetic moment norm of a permanent magnet. The models have been tested using an optical reference system for position and orientation estimation. Initial results are ambiguous and further testing is necessary. One conclusion is that the model using the magnetic moment vector as orientation parametrization is less sensitive to the accuracy of the initial guesses of the filter recursions and also less sensitive to possible model errors.

    A mathematical result of the possibility of using a non stationary sensor network to track the magnet is also given.

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    fulltext
  • 130.
    Aravkin, Aleksandr
    et al.
    University of Washington, USA.
    Burke, James V.
    University of Washington, USA.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Lozano, Aurelie
    IBM TJ Watson Research Centre, NY USA.
    Pillonetto, Gianluigi
    University of Padua, Italy.
    Generalized Kalman smoothing: Modeling and algorithms2017In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 86, p. 63-86Article in journal (Refereed)
    Abstract [en]

    State-space smoothing has found many applications in science and engineering. Under linear and Gaussian assumptions, smoothed estimates can be obtained using efficient recursions, for example Rauch Tung Striebel and Mayne Fraser algorithms. Such schemes are equivalent to linear algebraic techniques that minimize a convex quadratic objective function with structure induced by the dynamic model. These classical formulations fall short in many important circumstances. For instance, smoothers obtained using quadratic penalties can fail when outliers are present in the data, and cannot track impulsive inputs and abrupt state changes. Motivated by these shortcomings, generalized Kalman smoothing formulations have been proposed in the last few years, replacing quadratic models with more suitable, often nonsmooth, convex functions. In contrast to classical models, these general estimators require use of iterated algorithms, and these have received increased attention from control, signal processing, machine learning, and optimization communities. In this survey we show that the optimization viewpoint provides the control and signal processing community great freedom in the development of novel modeling and inference frameworks for dynamical systems. We discuss general statistical models for dynamic systems, making full use of nonsmooth convex penalties and constraints, and providing links to important models in signal processing and machine learning. We also survey optimization techniques for these formulations, paying close attention to dynamic problem structure. Modeling concepts and algorithms are illustrated with numerical examples. (C) 2017 Elsevier Ltd. All rights reserved.

  • 131. Order onlineBuy this publication >>
    Ardeshiri, Tohid
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Analytical Approximations for Bayesian Inference2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Bayesian inference is a statistical inference technique in which Bayes’ theorem is used to update the probability distribution of a random variable using observations. Except for few simple cases, expression of such probability distributions using compact analytical expressions is infeasible. Approximation methods are required to express the a priori knowledge about a random variable in form of prior distributions. Further approximations are needed to compute posterior distributions of the random variables using the observations. When the computational complexity of representation of such posteriors increases over time as in mixture models, approximations are required to reduce the complexity of such representations.

    This thesis further extends existing approximation methods for Bayesian inference, and generalizes the existing approximation methods in three aspects namely; prior selection, posterior evaluation given the observations and maintenance of computation complexity.

    Particularly, the maximum entropy properties of the first-order stable spline kernel for identification of linear time-invariant stable and causal systems are shown. Analytical approximations are used to express the prior knowledge about the properties of the impulse response of a linear time-invariant stable and causal system.

    Variational Bayes (VB) method is used to compute an approximate posterior in two inference problems. In the first problem, an approximate posterior for the state smoothing problem for linear statespace models with unknown and time-varying noise covariances is proposed. In the second problem, the VB method is used for approximate inference in state-space models with skewed measurement noise.

    Moreover, a novel approximation method for Bayesian inference is proposed. The proposed Bayesian inference technique is based on Taylor series approximation of the logarithm of the likelihood function. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions.

    Finally, two contributions are dedicated to the mixture reduction (MR) problem. The first contribution, generalize the existing MR algorithms for Gaussian mixtures to the exponential family of distributions and compares them in an extended target tracking scenario. The second contribution, proposes a new Gaussian mixture reduction algorithm which minimizes the reverse Kullback-Leibler divergence and has specific peak preserving properties.

    List of papers
    1. Maximum entropy properties of discrete-time first-order stable spline kernel
    Open this publication in new window or tab >>Maximum entropy properties of discrete-time first-order stable spline kernel
    Show others...
    2016 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 66, p. 34-38Article in journal (Refereed) Published
    Abstract [en]

    The first order stable spline (SS-1) kernel (also known as the tunedcorrelated kernel) is used extensively in regularized system identification, where the impulse response is modeled as a zero-mean Gaussian process whose covariance function is given by well designed and tuned kernels. In this paper, we discuss the maximum entropy properties of this kernel. In particular, we formulate the exact maximum entropy problem solved by the SS-1 kernel without Gaussian and uniform sampling assumptions. Under general sampling assumption, we also derive the special structure of the SS-1 kernel (e.g. its tridiagonal inverse and factorization have closed form expression), also giving to it a maximum entropy covariance completion interpretation.

    Keywords
    System identification;Regularization method;Kernel structure;Maximum entropy
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-121618 (URN)10.1016/j.automatica.2015.12.009 (DOI)
    Available from: 2015-09-28 Created: 2015-09-28 Last updated: 2017-12-01Bibliographically approved
    2. Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances
    Open this publication in new window or tab >>Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances
    2015 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, no 12, p. 2450-2454Article in journal (Refereed) Published
    Abstract [en]

    We present an adaptive smoother for linear state-space models with unknown process and measurement noise covariances. The proposed method utilizes the variational Bayes technique to perform approximate inference. The resulting smoother is computationally efficient, easy to implement, and can be applied to high dimensional linear systems. The performance of the algorithm is illustrated on a target tracking example.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2015
    Keywords
    Adaptive smoothing, Kalman filtering, noise covariance, Rauch-Tung-Striebel smoother, sensor calibration, time-varying noiseco variances, variational Bayes
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-121617 (URN)10.1109/LSP.2015.2490543 (DOI)000364207300007 ()
    Note

    At the time for thesis presentation publication was in status: Manuscript

    Available from: 2015-09-28 Created: 2015-09-28 Last updated: 2018-03-09Bibliographically approved
    3. Robust Inference for State-Space Models with Skewed Measurement Noise
    Open this publication in new window or tab >>Robust Inference for State-Space Models with Skewed Measurement Noise
    2015 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, no 11, p. 1898-1902Article in journal (Refereed) Published
    Abstract [en]

    Filtering and smoothing algorithms for linear discrete-time state-space models with skewed and heavy-tailed measurement noise are presented. The algorithms use a variational Bayes approximation of the posterior distribution of models that have normal prior and skew-t-distributed measurement noise. The proposed filter and smoother are compared with conventional low-complexity alternatives in a simulated pseudorange positioning scenario. In the simulations the proposed methods achieve better accuracy than the alternative methods, the computational complexity of the filter being roughly 5 to 10 times that of the Kalman filter.

    Place, publisher, year, edition, pages
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2015
    Keywords
    Kalman filter; robust filtering; RTS smoother; skew t; skewness; t-distribution; variational Bayes
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-120129 (URN)10.1109/LSP.2015.2437456 (DOI)000356458700003 ()
    Note

    Funding Agencies|Tampere University of Technology Graduate School; Finnish Doctoral Programme in Computational Sciences (FICS); Foundation of Nokia Corporation; Swedish research council (VR), project ETT [621-2010-4301]

    Available from: 2015-07-14 Created: 2015-07-13 Last updated: 2017-12-04
    4. Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family
    Open this publication in new window or tab >>Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, a Bayesian inference technique based on Taylor series approximation of the logarithm of the likelihood function is presented. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions. The logarithm of the likelihood function is linearized with respect to the sufficient statistic of the prior distribution in exponential family such that the posterior obtains the same exponential family form as the prior. Similarities between the proposed method and the extended Kalman filter for nonlinear filtering are illustrated. Further, an extended target measurement update for target models where the target extent is represented by a random matrix having an inverse Wishart distribution is derived. The approximate update covers the important case where the spread of measurement is due to the target extent as well as the measurement noise in the sensor.

    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-121616 (URN)
    Available from: 2015-09-28 Created: 2015-09-28 Last updated: 2015-10-05Bibliographically approved
    5. Greedy Reduction Algorithms for Mixtures of Exponential Family
    Open this publication in new window or tab >>Greedy Reduction Algorithms for Mixtures of Exponential Family
    2015 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, no 6, p. 676-680Article in journal (Refereed) Published
    Abstract [en]

    In this letter, we propose a general framework for greedy reduction of mixture densities of exponential family. The performances of the generalized algorithms are illustrated both on an artificial example where randomly generated mixture densities are reduced and on a target tracking scenario where the reduction is carried out in the recursion of a Gaussian inverse Wishart probability hypothesis density (PHD) filter.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2015
    Keywords
    Exponential family; extended target; integral square error; Kullback-Leibler divergence; mixture density; mixture reduction; target tracking
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-112990 (URN)10.1109/LSP.2014.2367154 (DOI)000345236400005 ()
    Note

    Funding Agencies|Swedish research council (VR) under ETT [621-2010-4301]; SSF, project CUAS

    Available from: 2015-01-12 Created: 2015-01-08 Last updated: 2017-12-05
    6. Gaussian Mixture Reduction Using Reverse Kullback-Leibler Divergence
    Open this publication in new window or tab >>Gaussian Mixture Reduction Using Reverse Kullback-Leibler Divergence
    (English)Manuscript (preprint) (Other academic)
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-121615 (URN)
    Available from: 2015-09-28 Created: 2015-09-28 Last updated: 2015-10-05
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  • 132.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Chen, Tianshi
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    MAXIMUM ENTROPY PROPERTY OF DISCRETE-TIME STABLE SPLINE KERNEL2015In: 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), IEEE , 2015, p. 3676-3680Conference paper (Refereed)
    Abstract [en]

    In this paper, the maximum entropy property of the discrete-time first-order stable spline kernel is studied. The advantages of studying this property in discrete-time domain instead of continuous-time domain are outlined. One of such advantages is that the differential entropy rate is well-defined for discrete-time stochastic processes. By formulating the maximum entropy problem for discrete-time stochastic processes we provide a simple and self-contained proof to show what maximum entropy property the discrete-time first-order stable spline kernel has.

  • 133.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Granström, Karl
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Orguner, Umut
    Middle E Technical University, Turkey.
    Greedy Reduction Algorithms for Mixtures of Exponential Family2015In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, no 6, p. 676-680Article in journal (Refereed)
    Abstract [en]

    In this letter, we propose a general framework for greedy reduction of mixture densities of exponential family. The performances of the generalized algorithms are illustrated both on an artificial example where randomly generated mixture densities are reduced and on a target tracking scenario where the reduction is carried out in the recursion of a Gaussian inverse Wishart probability hypothesis density (PHD) filter.

  • 134.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Larsson, Fredrik
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas B.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Bicycle Tracking Using Ellipse Extraction2011In: Proceedings of the 14thInternational Conference on Information Fusion, 2011, IEEE , 2011, p. 1-8Conference paper (Refereed)
    Abstract [en]

    A new approach to track bicycles from imagery sensor data is proposed. It is based on detecting ellipsoids in the images, and treat these pair-wise using a dynamic bicycle model. One important application area is in automotive collision avoidance systems, where no dedicated systems for bicyclists yet exist and where very few theoretical studies have been published.

    Possible conflicts can be predicted from the position and velocity state in the model, but also from the steering wheel articulation and roll angle that indicate yaw changes before the velocity vector changes. An algorithm is proposed which consists of an ellipsoid detection and estimation algorithm and a particle filter.

    A simulation study of three critical single target scenarios is presented, and the algorithm is shown to produce excellent state estimates. An experiment using a stationary camera and the particle filter for state estimation is performed and has shown encouraging results.

  • 135.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Löfberg, Johan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Convex Optimization Approach for Time-Optimal Path Tracking of Robots with Speed Dependent Constraints2010Report (Other academic)
    Abstract [en]

    The task of generating time optimal trajectories for a six degrees of freedom industrial robot is discussed and an existing convex optimization formulation of the problem is extended to include new types of constraints. The new constraints are speed dependent and can be motivated from physical modeling of the motors and the drive system. It is shown how the speed dependent constraints should be added in order to keep the convexity of the overall problem. A method to, conservatively, approximate the linear speed dependent constraints by a convex constraint is also proposed. A numerical example proves versatility of the extension proposed in this paper.

    Download full text (pdf)
    FULLTEXT01
  • 136.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Löfberg, Johan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Convex Optimization Approach for Time-Optimal Path Tracking of Robots with Speed Dependent Constraints2011In: Proceedings of the 18th IFAC World Congress, IFAC , 2011, p. 14648-14653Conference paper (Refereed)
    Abstract [en]

    The task of generating time optimal trajectories for a six degrees of freedom industrial robot is discussed and an existing convex optimization formulation of the problem is extended to include new types of constraints. The new constraints are speed dependent and can be motivated from physical modeling of the motors and the drive system. It is shown how the speed dependent constraints should be added in order to keep the convexity of the overall problem. A method to, conservatively, approximate the linear speed dependent constraints by a convex constraint is also proposed. A numerical example proves versatility of the extension proposed in this paper.

    Download full text (pdf)
    T-Optimal_IFAC-WC2011
  • 137.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nurminen, Henri
    Department of Automation Science and Engineering, Tampere University of Technology, Finland.
    Pichè, Robert
    Department of Automation Science and Engineering, Tampere University of Technology, Finland.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Variational Iterations for Filtering and Smoothing with skew-t measurement noise2015Report (Other academic)
    Abstract [en]

    In this technical report, some derivations for the filter and smoother proposed in [1] are presented. More specifically, the derivations for the cyclic iteration needed to solve the variational Bayes filter and smoother for state space models with skew t likelihood proposed in [1] are presented.

    Download full text (pdf)
    fulltext
  • 138.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential FamilyManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, a Bayesian inference technique based on Taylor series approximation of the logarithm of the likelihood function is presented. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions. The logarithm of the likelihood function is linearized with respect to the sufficient statistic of the prior distribution in exponential family such that the posterior obtains the same exponential family form as the prior. Similarities between the proposed method and the extended Kalman filter for nonlinear filtering are illustrated. Further, an extended target measurement update for target models where the target extent is represented by a random matrix having an inverse Wishart distribution is derived. The approximate update covers the important case where the spread of measurement is due to the target extent as well as the measurement noise in the sensor.

  • 139.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Orguner, Umut
    Middle East Technical University.
    Lundquist, Christian
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On mixture reduction for multiple target tracking2012Conference paper (Refereed)
    Download full text (pdf)
    MR2012
  • 140.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Orguner, Umut
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Gaussian Mixture Reduction Using Reverse Kullback-Leibler DivergenceManuscript (preprint) (Other academic)
  • 141.
    Ardeshiri, Tohid
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control.
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    An adaptive PHD filter for tracking with unknown sensor characteristics2013Conference paper (Refereed)
    Abstract [en]

    In multi-target tracking, the discrepancy between the nominal and the true values of the model parameters might result in poor performance. In this paper, an adaptive Probability Hypothesis Density (PHD) filter is proposed which accounts for sensor parameter uncertainty. Variational Bayes technique is used for approximate inference which provides analytic expressions for the PHD recursions analogous to the Gaussian mixture implementation of the PHD filter. The proposed method is evaluated in a multi-target tracking scenario. The improvement in the performance is shown in simulations.

    Download full text (pdf)
    VBPHD
  • 142.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Orguner, Umut
    Middle East Technical University.
    On Reduction of Mixtures of the Exponential Family Distributions2013Report (Other academic)
    Abstract [en]

    Many estimation problems require a mixture reduction algorithm with which an increasing number of mixture components are reduced to a tractable level. In this technical report a discussion on dierent aspects of mixture reduction is given followed by a presentation of numerical simulation on reduction of mixture densities where the component density belongs to the exponential family of distributions.

    Download full text (pdf)
    On Reduction of Mixtures of the Exponential Family Distributions
  • 143.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances2015In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, no 12, p. 2450-2454Article in journal (Refereed)
    Abstract [en]

    We present an adaptive smoother for linear state-space models with unknown process and measurement noise covariances. The proposed method utilizes the variational Bayes technique to perform approximate inference. The resulting smoother is computationally efficient, easy to implement, and can be applied to high dimensional linear systems. The performance of the algorithm is illustrated on a target tracking example.

  • 144.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Variational Iterations for Smoothing with Unknown Process and Measurement Noise Covariances2015Report (Other academic)
    Abstract [en]

    In this technical report, some derivations for the smoother proposed in [1] are presented. More specifically, the derivations for the cyclic iteration needed to solve the variational Bayes smoother for linear state-space models with unknownprocess and measurement noise covariances in [1] are presented. Further, the variational iterations are compared with iterations of the Expectation Maximization (EM) algorithm for smoothing linear state-space models with unknown noise covariances.

    [1] T. Ardeshiri, E. Özkan, U. Orguner, and F. Gustafsson, ApproximateBayesian smoothing with unknown process and measurement noise covariances, submitted to Signal Processing Letters, 2015.

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  • 145.
    Arkad, Jenny
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Andersson, Tomas
    Linköping University, Department of Electrical Engineering, Automatic Control.
    A Control Algorithm for an Ultrasonic Motor2011Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This report is the result of a master thesis work where the goal was to develop acontrol system for a type of ultrasonic motor. The ultrasonic motors use ultrasonicvibrations from a piezoelectric material to produce a rotating motion. They arepowered by two sinusoidal voltages and their control signals generally are thevoltages amplitude, frequency and the phase difference between the two voltages.In this work the focus is on control using only amplitude and frequency. A feedbacksignal was provided by an encoder, giving an angular position. The behavior of themotors were investigated for various sets of control signals. From collected data alinearized static model was derived for the motor speed. This derived model wasused to create a two part control system, with an inner control loop to managethe speed of the motors using a PI controller and an outer control loop to managethe position of the motors. A simple algorithm was used for the position controland the result was a control system able to position the motors with a 0.1 degreeaccuracy. The motors show potential for greater accuracy with a position feedback,but the result in this work is limited by the encoder used in the experiments.

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    USM_control
  • 146.
    Armstrong, Perry
    et al.
    Queens University Belfast, United Kingdom.
    Bankel, Johan
    Chalmers University of Technology, Sweden.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Keesee, John
    Massachusetts Institute of Technology, USA.
    Oosthuizen, Pat
    Queens University, Canada.
    Meeting the CDIO Requirements: An International Comparison of Engineering Curricula2006In: World Transactions on Engineering and Technology Education, ISSN 1446-2257, Vol. 5, no 2, p. 263-266Article in journal (Refereed)
    Abstract [en]

    In this article, the Conceive – Design – Implement – Operate (CDIO) Syllabus and CDIO Standards are introduced, and the question is posed as to whether or not national circumstances affect the ability of engineering programmes to meet CDIOrequirements. In particular, the extent to which representative programmes from the USA, Canada, Sweden and the UK cover the CDIO Syllabus is assessed and conclusions are drawn. The international applicability of the CDIO Syllabus also depends on the absence of conflict between the syllabus and national accreditation criteria. Based on the countries considered, the authors suggest that no conflict exists. Furthermore, it is argued that the CDIO Syllabus is aspirational and, as such, it complements the threshold requirements of national accreditation criteria. It is also argued that the CDIO Syllabus, coupled with the CDIO Standards, could form the basis for an international benchmark that would co-exist with any future global accreditation criteria and would serve to continuously improve engineering education.

  • 147.
    Arnström, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control.
    State Estimation for Truck and Trailer Systems using Deep Learning2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    High precision control of a truck and trailer system requires accurate and robust state estimation of the system.

    This thesis work explores the possibility of estimating the states with high accuracy from sensors solely mounted on the truck. The sensors used are a LIDAR sensor, a rear-view camera and a RTK-GNSS receiver.

    Information about the angles between the truck and the trailer are extracted from LIDAR scans and camera images through deep learning and through model-based approaches. The estimates are fused together with a model of the dynamics of the system in an Extended Kalman Filter to obtain high precision state estimates. Training data for the deep learning approaches and data to evaluate and compare these methods with the model-based approaches are collected in a simulation environment established in Gazebo.

    The deep learning approaches are shown to give decent angle estimations but the model-based approaches are shown to result in more robust and accurate estimates. The flexibility of the deep learning approach to learn any model given sufficient training data has been highlighted and it is shown that a deep learning approach can be viable if the trailer has an irregular shape and a large amount of data is available.

    It is also shown that biases in measured lengths of the system can be remedied by estimating the biases online in the filter and this improves the state estimates.

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  • 148.
    Arvidsson, Marcus
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Attenuation of Harmonic Distortion in Loudspeakers Using Non-linear Control2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The first loudspeaker was invented almost 150 years ago and even though much has changed regarding the manufacturing, the main idea is still the same. To produce clean sound, modern loudspeaker consist of expensive materials that often need advanced manufacturing equipment. The relatively newly established company Actiwave AB uses digital signal processing to enhance the audio for loudspeakers with poor acoustic properties. Their algorithms concentrate on attenuating the linear distortion but there is no compensation for the loudspeakers' non-linear distortion, such as harmonic distortion.

    To attenuate the harmonic distortion, this thesis presents controllers based on exact input-output linearisation. This type of controller needs an accurate model of the system. A loudspeaker model has been derived based on the LR-2 model, an extension of the more common Thiele-Small model.

    A controller based on exact input-output linearisation also needs full state feedback, but since feedback risk being expensive, state estimators were used. The state estimators were based on feed-forward or observers using the extended Kalman filter or the unscented Kalman filter. A combination of feed-forward state estimation and a PID controller were designed as well.

    In simulations, the total harmonic distortion was attenuated for all controllers up to 180 Hz. The simulations also showed that the controllers are sensitive to inaccurate parameter values in the loudspeaker model. During real-life experiments, the controllers needed to be extended with a model of the used amplifier to function properly. The controllers that were able to attenuate the harmonic distortion were the two methods using feed-forward state estimation. Both controllers showed improvement compared to the uncontrolled case for frequencies up to 40 Hz.

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  • 149. Order onlineBuy this publication >>
    Axehill, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Applications of Integer Quadratic Programming in Control and Communication2005Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control principles is the discrete-time method Model Predictive Control (MPC). The main advantage with MPC, compared to most other control principles, is that constraints on control signals and states can easily be handled. In each time step, MPC requires the solution of a Quadratic Programming (QP) problem. To be able to use MPC for large systems, and at high sampling rates, optimization routines tailored for MPC are used. In recent years, the range of application of MPC has been extended from constrained linear systems to so-called hybrid systems. Hybrid systems are systems where continuous dynamics interact with logic. When this extension is made, binary variables are introduced in the problem. As a consequence, the QP problem has to be replaced by a far more challenging Mixed Integer Quadratic Programming (MIQP) problem. Generally, for this type of optimization problems, the computational complexity is exponential in the number of binary optimization variables. In modern communication systems, multiple users share a so-called multi-access channel, where the information sent by different users is separated by using almost orthogonal codes. Since the codes are not completely orthogonal, the decoded information at the receiver is slightly correlated between different users. Further, noise is added during the transmission. To estimate the information originally sent, a maximum likelihood problem involving binary variables is solved. The process of simultaneously estimating the information sent by multiple users is called multiuser detection. In this thesis, the problem to efficiently solve MIQP problems originating from MPC is addressed. Two different algorithms are presented. First, a polynomial complexity preprocessing algorithm for binary quadratic programming problems is presented. By using the algorithm, some, or all, binary variables can be computed efficiently already in the preprocessing phase. In simulations, the algorithm is applied to unconstrained MPC problems with a mixture of real and binary control signals. It has also been applied to the multiuser detection problem, where simulations have shown that the bit error rate can be significantly reduced by using the proposed algorithm as compared to using common suboptimal algorithms. Second, an MIQP algorithm tailored for MPC is presented. The algorithm uses a branch and bound method where the relaxed node problems are solved by a dual active set QP algorithm. In this QP algorithm, the KKT-systems are solved using Riccati recursions in order to decrease the computational complexity. Simulation results show that both the QP solver and the MIQP solver proposed have lower computational complexity than corresponding generic solvers.

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    FULLTEXT01
  • 150.
    Axehill, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Att handleda en uppgift utan facit2007Report (Other academic)
    Download full text (pdf)
    FULLTEXT01
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