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  • 1.
    Abara, Precious Ugo
    et al.
    Univ Padua, Italy; Tech Univ Munich, Germany.
    Ticozzi, Francesco
    Univ Padua, Italy; Dartmouth Coll, NH 03755 USA.
    Altafini, Claudio
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Spectral Conditions for Stability and Stabilization of Positive Equilibria for a Class of Nonlinear Cooperative Systems2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 2, p. 402-417Article in journal (Refereed)
    Abstract [en]

    Nonlinear cooperative systems associated to vector fields that are concave or subhomogeneous describe well interconnected dynamics that are of key interest for communication, biological, economical, and neural network applications. For this class of positive systems, we provide conditions that guarantee existence, uniqueness and stability of strictly positive equilibria. These conditions can be formulated directly in terms of the spectral radius of the Jacobian of the system. If control inputs are available, then it is shown how to use state feedback to stabilize an equilibrium point in the interior of the positive orthant.

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  • 2.
    Aberger, Martin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Effects of Nonlinearities in Black Box Identification of an Industrial Robot2000Report (Other academic)
    Abstract [en]

    This paper discusses effects of nonlinearities in black box identification of one axis of a robot. The used data come from a commercial ABB robot, IRB1400. A three-mass flexible model for the robot was built in MathModelica. The nonlinearities in the model are nonlinear friction and backlash in the gear box.

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  • 3.
    Abrahamsson, Henrik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Carlson, Peter
    Linköping University, The Institute of Technology.
    Robust Torque Control for Automated Gear Shifting in Heavy Duty Vehicles2008Independent thesis Advanced level (professional degree), 20 points / 30 hpStudent thesis
    Abstract [en]

    In an automated manual transmission it is desired to have zero torque in the transmission when disengaging a gear. This minimizes the oscillations in the driveline which increases the comfort and makes the speed synchronization easier. The automated manual transmission system in a Scania truck, called Opticruise, uses engine torque control to achieve zero torque in the transmission.In this thesis different control strategies for engine torque control are proposed in order to minimize the oscillations in the driveline and increase the comfort during a gear shift. A model of the driveline is developed in order to evaluate the control strategies. The main focus was to develop controllers that are easy to implement and that are robust enough to be used in different driveline configurations. This means that model dependent control strategies are not considered.A control strategy with a combination of a feedback from the speed difference between the output shaft speed and the wheel speed, and a feedforward with a linear ramp, showed very good performance in both simulations and tests in trucks. The amplitude of the oscillations in the output shaft speed after neutralengagement are halved compared to the results from the existing method in Scania trucks. The new concept is also more robust against initial conditions and time delay estimations.

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  • 4.
    Abrahamsson, Per
    Linköping University, Department of Electrical Engineering.
    Combined Platform for Boost Guidance and Attitude Control for Sounding Rockets2004Independent thesis Basic level (professional degree)Student thesis
    Abstract [en]

    This report handles the preliminary design of a control system that includes both attitude control and boost control functionality for sounding rockets. This is done to reduce the weight and volume for the control system.

    A sounding rocket is a small rocket compared to a satellite launcher. It is used to launch payloads into suborbital trajectories. The payload consists of scientific experiments, for example micro-gravity experiments and astronomic observations. The boost guidance system controls the sounding rocket during the launch phase. This is done to minimize the impact dispersion. The attitude control system controls the payload during the experiment phase.

    The system that is developed in this report is based on the DS19 boost guidance system from Saab Ericsson Space AB. The new system is designed by extending DS19 with software and hardware. The new system is therefore named DS19+. Hardware wise a study of the mechanical and electrical interfaces and also of the system budgets for gas, mass and power for the system are done to determine the feasibility for the combined system.

    Further a preliminary design of the control software is done. The design has been implemented as pseudo code in MATLAB for testing and simulations. A simulation model for the sounding rocket andits surroundings during the experiment phase has also been designed and implemented in MATLAB. The tests and simulations that have been performed show that the code is suitable for implementation in the real system.

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  • 5.
    Abrahamsson, Thomas
    et al.
    Saab Military Aircraft, Sweden.
    Andersson, Magnus
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    McKelvey, Tomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Finite Element Model Updating Formulation Using Frequency Responses and Eigenfrequencies1996Report (Other academic)
    Abstract [en]

    A novel frequency and modal domain formulation of the model updating problem is presented. Deviations in discrete frequency responses and eigenfrequencies, between the model to be updated and a reference model, constitute the criterion function. A successful updating thus results in a model with the reference's input-output relations at selected fre- quencies. The formulation is demonstrated to produce a criterion function with a global minimum having a large domain of attraction with respect to stiffness and mass variations. The method relies on mode grouping and uses a new extended modal assurance criterion number (eMAC) for identifying related modes. A quadratic objective with inexpensive evaluation of approximate Hessians give a rapid convergence to a minimum by the use of a regularized Gauss-Newton method. Physical bounds on parameters and complementary data, such as structural weight, are treated by imposing set constraints and linear equality constraints. Efficient function computation is obtained by model reduction using a moderately sized base of modes which is recomputed during the minimization. Statistical properties of updated parameters are discussed. A verification example show the performance of the method.

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  • 6.
    Abrahamsson, Tomas
    et al.
    Saab Military Aircraft, Sweden.
    McKelvey, Tomas
    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.
    A Study of some Approaches to Vibration Data Analysis1993Report (Other academic)
    Abstract [en]

    Using data from extensive vibrational tests of the new aircraft Saab 2000 three different methods for vibration analysis are studied. These methods are ERA (eigensystem realization algorithm), N4SID (a subspace method) and PEM (prediction error approach). We find that both the ERA and N4SID methods give good initial model parameter estimates that can be further improved by the use of PEM. We also find that all methods give good insights into the vibrational modes.

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  • 7.
    Adib Yaghmaie, Farnaz
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    A New Result on Robust Adaptive Dynamic Programming for Uncertain Partially Linear Systems2019In: 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2019, p. 7480-7485Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a new result on robust adaptive dynamic programming for the Linear Quadratic Regulation (LQR) problem, where the linear system is subject to unmatched uncertainty. We assume that the states of the linear system are fully measurable and the matched uncertainty models unmeasurable states with an unspecified dimension. We use the small-gain theorem to give a sufficient condition such that the generated policies in each iteration of on-policy and off-policy routines guarantee robust stability of the overall uncertain system. The sufficient condition can be used to design the weighting matrices in the LQR problem. We use a simulation example to demonstrate the result.

  • 8.
    Adib Yaghmaie, Farnaz
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Lewis, Frank L.
    Univ Texas Arlington, TX 76019 USA; Northeastern Univ, Peoples R China.
    Output regulation of unknown linear systems using average cost reinforcement learning2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 110, article id 108549Article in journal (Refereed)
    Abstract [en]

    In this paper, we introduce an optimal average cost learning framework to solve output regulation problem for linear systems with unknown dynamics. Our optimal framework aims to design the controller to achieve output tracking and disturbance rejection while minimizing the average cost. We derive the Hamilton-Jacobi-Bellman (HJB) equation for the optimal average cost problem and develop a reinforcement algorithm to solve it. Our proposed algorithm is an off-policy routine which learns the optimal average cost solution completely model-free. We rigorously analyze the convergence of the proposed algorithm. Compared to previous approaches for optimal tracking controller design, we elevate the need for judicious selection of the discounting factor and the proposed algorithm can be implemented completely model-free. We support our theoretical results with a simulation example. (C) 2019 Elsevier Ltd. All rights reserved.

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  • 9.
    Adib Yaghmaie, Farnaz
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Using Reinforcement Learning for Model-free Linear Quadratic Control with Process and Measurement Noises2019In: 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2019, p. 6510-6517Conference paper (Refereed)
    Abstract [en]

    In this paper, we analyze a Linear Quadratic (LQ) control problem in terms of the average cost and the structure of the value function. We develop a completely model-free reinforcement learning algorithm to solve the LQ problem. Our algorithm is an off-policy routine where each policy is greedy with respect to all previous value functions. We prove that the algorithm produces stable policies given that the estimation errors remain small. Empirically, our algorithm outperforms the classical Q and off-policy learning routines.

  • 10.
    Adib Yaghmaie, Farnaz
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Linear Quadratic Control Using Model-Free Reinforcement Learning2023In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 68, no 2, p. 737-752Article in journal (Refereed)
    Abstract [en]

    In this article, we consider linear quadratic (LQ) control problem with process and measurement noises. We analyze the LQ problem in terms of the average cost and the structure of the value function. We assume that the dynamics of the linear system is unknown and only noisy measurements of the state variable are available. Using noisy measurements of the state variable, we propose two model-free iterative algorithms to solve the LQ problem. The proposed algorithms are variants of policy iteration routine where the policy is greedy with respect to the average of all previous iterations. We rigorously analyze the properties of the proposed algorithms, including stability of the generated controllers and convergence. We analyze the effect of measurement noise on the performance of the proposed algorithms, the classical off-policy, and the classical Q-learning routines. We also investigate a model-building approach, inspired by adaptive control, where a model of the dynamical system is estimated and the optimal control problem is solved assuming that the estimated model is the true model. We use a benchmark to evaluate and compare our proposed algorithms with the classical off-policy, the classical Q-learning, and the policy gradient. We show that our model-building approach performs nearly identical to the analytical solution and our proposed policy iteration based algorithms outperform the classical off-policy and the classical Q-learning algorithms on this benchmark but do not outperform the model-building approach.

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  • 11.
    Adib Yaghmaie, Farnaz
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Modares, Hamidreza
    Michigan State University, USA.
    Online Optimal Tracking of Linear Systems with Adversarial Disturbances2023In: Transactions on Machine Learning Research, E-ISSN 2835-8856, no 04Article in journal (Refereed)
    Abstract [en]

    This paper presents a memory-augmented control solution to the optimal reference tracking problem for linear systems subject to adversarial disturbances. We assume that the dynamics of the linear system are known and that the reference signal is generated by a linear system with unknown dynamics. Under these assumptions, finding the optimal tracking controller is formalized as an online convex optimization problem that leverages memory of past disturbance and reference values to capture their temporal effects on the performance. That is, a (disturbance, reference)-action control policy is formalized, which selects the control actions as a linear map of the past disturbance and reference values. The online convex optimization is then formulated over the parameters of the policy on its past disturbance and reference values to optimize general convex costs. It is shown that our approach outperforms robust control methods and achieves a tight regret bound O(√T) where in our regret analysis, we have benchmarked against the best linear policy.

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  • 12.
    Adib Yaghmaie, Farnaz
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Modares, Hamidreza
    Michigan State Univ, MI 48824 USA.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Reinforcement Learning for Partially Observable Linear Gaussian Systems Using Batch Dynamics of Noisy Observations2024In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 69, no 9, p. 6397-6404Article in journal (Refereed)
    Abstract [en]

    Reinforcement learning algorithms are commonly used to control dynamical systems with measurable state variables. If the dynamical system is partially observable, reinforcement learning algorithms are modified to compensate for the effect of partial observability. One common approach is to feed a finite history of input-output data instead of the state variable. In this article, we study and quantify the effect of this approach in linear Gaussian systems with quadratic costs. We coin the concept of L-Extra-Sampled-dynamics to formalize the idea of using a finite history of input-output data instead of state and show that this approach increases the average cost.

  • 13.
    Adén, Sebastian
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Modellbaserad diagnostik tillämpad för hydrauliska applikationer2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [sv]

    I en globaliserad värld där produktägare finner sina produkter på alltmer avslägsna platser, ökar behovet av att på ett så ekonomiskt och tidseffektivt sätt som möjligt, utföra reperationer och underhållningsarbeten. Att erbjuda en stark och mer effektiv eftermarknadssupport kan öka företagens konkurrenskraft och framför allt göra dem kostnadseffektiva med avseende på lägre bemanningsstyrka. Ett sätt att underlätta underhållningsarbetet är genom att använda modellbaserad diagnos för att generera underlag vid exempelvis reperationsarbeten.

    Denna rapport undersöker möjligheterna att utifrån en modell av en hydraulisk applikation, utföra autogenererad diagnostik bland annat iform av felträdsanalys.

    Innehållet i rapporten beskriver även hur modelleringsarbetet har gått till och utveckling av modellens ingående komponenter.

    Examensarbetet är utfört på Combitech AB, Linköping. 

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  • 14.
    Afsarinejad, Arash
    Linköping University, Department of Electrical Engineering.
    Synkronisering med SyncML2002Independent thesis Basic level (professional degree)Student thesis
    Abstract [en]

    The last couple of years the use of mobile devices such as mobile phones and PDAs has increased tremendously. Most of the these devices have their own protocols for synchronising data and this has given rise to a need for a standard synchronisation protocol, SyncML. This thesis compares this protocol against the existing ones. The comparison shows that the preferred choice is SyncML.

    Also an application using SyncML has been developed. The application's task is to synchronise the calendar on a mobile phone with a database on a computer.

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  • 15.
    Agardt, Erik
    et al.
    Linköping University, Department of Electrical Engineering.
    Löfgren, Markus
    Linköping University, Department of Electrical Engineering.
    Pilot Study of Systems to Drive Autonomous Vehicles on Test Tracks2008Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This Master’s thesis is a pilot study that investigates different systems to drive autonomous and non-autonomous vehicles simultaneously on test tracks. The thesis includes studies of communication, positioning, collision avoidance, and techniques for surveillance of vehicles which are suitable for implementation. The investigation results in a suggested system outline.

    Differential GPS combined with laser scanner vision is used for vehicle state estimation (position, heading, velocity, etc.). The state information is transmitted with IEEE 802.11 to all surrounding vehicles and surveillance center. With this information a Kalman prediction of the future position for all vehicles can be estimated and used for collision avoidance.

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  • 16.
    Agebjär, Martin
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Model-Based Road Roughness Estimation2024Independent thesis Advanced level (degree of Master (Two Years)), 28 HE creditsStudent thesis
    Abstract [en]

    Road roughness is the primary source of vehicle vibrations. This thesis investigates model-based methods for estimating road roughness in terms of the International Roughness Index (IRI) by measuring the chassis vibrations of the vehicle. This can provide NIRA Dynamics AB with a cost-effective pavement monitoring solution.

    Initially, system identification is performed on a physical car to estimate model parameters that reflect reality. Subsequently, two model-based IRI estimation methods are developed. One method relies on a transfer function between vertical chassis vibrations and the IRI according to a quarter-car model. The second method aims first to estimate the longitudinal road profile using a Kalman filter, and then calculate the IRI values from the estimated profile. This method can be implemented computationally efficiently and also offers the possibility of estimating the IRI using lateral vibrations. Both methods are validated using real-world data, and their performance is similar when using vertical vibrations, with the IRI estimation error’s standard deviation being roughly 10% to 20% of the reference value. However, the results are considerably worse when the estimation is purely based on lateral vibrations, indicating that lateral vibrations are not feasible for model-based IRI estimation, and the reasons for this are discussed.

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  • 17.
    Ahlberg, Jörgen
    et al.
    Swedish Defence Research Agency, Sweden.
    Folkesson, Martin
    Swedish Defence Research Agency, Sweden.
    Grönwall, Christina
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Horney, Tobias
    Swedish Defence Research Agency, Sweden.
    Jungert, Erland
    Swedish Defence Research Agency, Sweden.
    Klasén, Lena
    Swedish Defence Research Agency, Sweden.
    Ulvklo, Morgan
    Swedish Defence Research Agency, Sweden.
    Ground Target Recognition in a Query-Based Multi-Sensor Information System2006Report (Other academic)
    Abstract [en]

    We present a system covering the complete process for automatic ground target recognition, from sensor data to the user interface, i.e., from low level image processing to high level situation analysis. The system is based on a query language and a query processor, and includes target detection, target recognition, data fusion, presentation and situation analysis. This paper focuses on target recognition and its interaction with the query processor. The target recognitionis executed in sensor nodes, each containing a sensor and the corresponding signal/image processing algorithms. New sensors and algorithms are easily added to the system. The processing of sensor data is performed in two steps; attribute estimation and matching. First, several attributes, like orientation and dimensions, are estimated from the (unknown but detected) targets. These estimates are used to select the models of interest in a matching step, where the targetis matched with a number of target models. Several methods and sensor data types are used in both steps, and data is fused after each step. Experiments have been performed using sensor data from laser radar, thermal and visual cameras. Promising results are reported, demonstrating the capabilities of the target recognition algorithms, the advantages of the two-level data fusion and the query-based system.

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  • 18.
    Ahlin, Karl
    Linköping University, Department of Electrical Engineering.
    Quality of Service i IP-nätverk2003Independent thesis Basic level (professional degree)Student thesis
    Abstract [en]

    The original promise behind the Internet Protocol was to deliver data from a sender to the receiver using a best-effort approach. This means that the protocol makes no guarantees except that it will try to deliver the data to the destination. If some problem occurs the packet may be discarded by the network without any notice. No guarantees are made regarding the time it takes to deliver the data, the rate at which data will be delivered or if data is delivered in the same order it was sent. The best-effort approach is arguably the reason behind the success of the Internet Protocol and is what makes IP scalable to networks the size of the Internet. However, this approach is also a problem for network operators who want to offer better quality of service to some of their customers. This master thesis will discuss some of the theories behind the implementation of quality of service schemes in an IP network and also provide an example of how to implement it in an existing network.

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  • 19.
    Ahlström, Linus
    Linköping University, Department of Electrical Engineering.
    Algoritmer för objektdetektering i SAR och IR-bilder2003Independent thesis Basic level (professional degree)Student thesis
    Abstract [en]

    The first part of the thesis consists of a brief introduction to the general principles of target detection and the sensor-systems used. In the following part there is a theoretical description of the algorithms this thesis focuses on. The detection algorithms described in this paper are called Cell Average, Ordered Statistics, 2parameter and Gammadetector. Two different discriminators called Extended Fractal Features and Quadratic Gamma Discriminator are also described. The algorithms are tested on three different types of data, simulated SAR-pictures, authentic SAR-targets and IR-pictures. The last part account for the results, both those achieved with pictures and those results achieved when doing statistical tests, in this case MonteCarlo- simulations and Reciever Operating Characteristics-curves. The results show that the Gamma- detector and the QGD-algorithm perform best on the tests done in this thesis.

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  • 20.
    Ahmadi, Shervin Parvini
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    A Distributed Second-Order Augmented Lagrangian Method for Distributed Model Predictive Control2021In: IFAC PAPERSONLINE, ELSEVIER , 2021, Vol. 54, no 6, p. 192-199Conference paper (Refereed)
    Abstract [en]

    In this paper we present a distributed second-order augmented Lagrangian method for distributed model predictive control. We distribute the computations for search direction, step size, and termination criteria over what is known as the clique tree of the problem and calculate each of them using message passing. The algorithm converges to its centralized counterpart and it requires fewer communications between sub-systems as compared to algorithms such as the alternating direction method of multipliers. Results from a simulation study confirm the efficiency of the framework. Copyright (C) 2021 The Authors.

  • 21.
    Ahmadi, Shervin Parvini
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Parallel Exploitation for Tree-Structured Coupled Quadratic Programming in Julia2018In: Proceedings of the 22nd International Conference on System Theory, Control and Computing, IEEE, 2018, p. 597-602Conference paper (Refereed)
    Abstract [en]

    The main idea in this paper is to implement a distributed primal-dual interior-point algorithm for loosely coupled Quadratic Programming problems. We implement this in Julia and show how can we exploit parallelism in order to increase the computational speed. We investigate the performance of the algorithm on a Model Predictive Control problem.

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  • 22.
    Ahmadi, Shervin Parvini
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Pakazad, Sina Khoshfetrat
    C3 IoT, CA USA.
    Efficient Robust Model Predictive Control using Chordality2019In: 2019 18TH EUROPEAN CONTROL CONFERENCE (ECC), IEEE , 2019, p. 4270-4275Conference paper (Refereed)
    Abstract [en]

    In this paper we show that chordal structure can be used to devise efficient optimization methods for robust model predictive control problems. To this end, first the problem is converted to an equivalent robust quadratic programming formulation. We then illustrate how the chordal structure can be used to distribute the computations in a primal-dual interior-point method among computational agents, which in turn allows us to accelerate the algorithm by efficient parallel computations. We investigate performance of the framework in Julia using numerical examples.

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  • 23.
    Aihara, ShinIchi
    et al.
    Tokyo University of Science, Japan.
    Bagch, Arunabha
    Twente University, Netherlands.
    Saha, Saikat
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification of Bates Stochastic Volatility Model by Using Non-Central Chi-Square Random Generation Method2012In: Proceedings of the 37th IEEE International Conference on Acoustics, Speech, and Signal Processing, 2012, , p. 4p. 3905-3908Conference paper (Refereed)
    Abstract [en]

    We study the identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility and its systems parameters is constructed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.

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  • 24.
    Aili, Adam
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Ekelund, Erik
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Model-Based Design, Development and Control of an Underwater Vehicle2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the rising popularity of ROVs and other UV solutions, more robust and high performance controllers have become a necessity. A model of the ROV or UV can be a valuable tool during control synthesis. The main objective of this thesis was to use a model in design and development of controllers for an ROV.

    In this thesis, an ROV from Blue Robotics was used. The ROV was equipped with 6 thrusters placed such that the ROV was capable of moving in 6-DOFs. The ROV was further equipped with an IMU, two pressure sensors and a magnetometer. The ROV platform was further developed with EKF-based sensor fusion, a control system and manual control capabilities.

    To model the ROV, the framework of Fossen (2011) was used. The model was estimated using two different methods, the prediction-error method and an EKF-based method. Using the prediction-error method, it was found that the initial states of the quaternions had a large impact on the estimated parameters and the overall fit to validation data. A Kalman smoother was used to estimate the initial states. To circumvent the problems with the initial quaternions, an \abbrEKF was implemented to estimate the model parameters. The EKF estimator was less sensitive to deviations in the initial states and produced a better result than the prediction-error method. The resulting model was compared to validation data and described the angular velocities well with around 70 % fit.

    The estimated model was used to implement feedback linearisation which was used in conjunction with an attitude controller and an angular velocity controller. Furthermore, a depth controller was developed and tuned without the use of the model. Performance of the controllers was tested both in real tests and simulations. The angular velocity controller using feedback linearisation achieved good reference tracking. However, the attitude controller could not stabilise the system while using feedback linearisation. Both controllers' performance could be improved further by tuning the controllers' parameters during tests.

    The fact that the feedback linearisation made the ROV unstable, indicates that the attitude model is not good enough for use in feedback linearisation. To achieve stability, the magnitude of the parameters in the feedback linearisation were scaled down. The assumption that the ROV's center of rotation coincides with the placement of the ROV's center of gravity was presented as a possible source of error.

    In conclusion, good performance was achieved using the angular velocity controller. The ROV was easier to control with the angular velocity controller engaged compared to controlling it in open loop. More work is needed with the model to get acceptable performance from the attitude controller. Experiments to estimate the center of rotation and the center of gravity of the ROV may be helpful when further improving the model.

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  • 25.
    Akin, Bilal
    et al.
    Texas Instruments Inc, USA.
    Choi, Seungdeog
    Texas A&M University, USA.
    Orguner, Umut
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Toliyat, Hamid A
    Texas A&M University, USA.
    A Simple Real-Time Fault Signature Monitoring Tool for Motor-Drive-Embedded Fault Diagnosis Systems2011In: IEEE Transactions on Industrial Electronics, ISSN 0278-0046, E-ISSN 1557-9948, Vol. 58, no 5, p. 1990-2001Article in journal (Refereed)
    Abstract [en]

    The reference frame theory constitutes an essential aspect of electric machine analysis and control. In this study, apart from the conventional applications, it is reported that the reference frame theory approach can successfully be applied to real-time fault diagnosis of electric machinery systems as a powerful toolbox to find the magnitude and phase quantities of fault signatures with good precision as well. The basic idea is to convert the associated fault signature to a dc quantity, followed by the computation of the signals average in the fault reference frame to filter out the rest of the signal harmonics, i.e., its ac components. As a natural consequence of this, neither a notch filter nor a low-pass filter is required to eliminate fundamental component or noise content. Since the incipient fault mechanisms have been studied for a long time, the motor fault signature frequencies and fault models are very well-known. Therefore, ignoring all other components, the proposed method focuses only on certain fault signatures in the current spectrum depending on the examined motor fault. Broken rotor bar and eccentricity faults are experimentally tested online using a TMS320F2812 digital signal processor (DSP) to prove the effectiveness of the proposed method. In this application, only the readily available drive hardware is used without employing additional components such as analog filters, signal conditioning board, external sensors, etc. As the motor drive processing unit, the DSP is utilized both for motor control and fault detection purposes, providing instantaneous fault information. The proposed algorithm processes the measured data in real time to avoid buffering and large-size memory needed in order to enhance the practicability of this method. Due to the short-time convergence capability of the algorithm, the fault status is updated in each second. The immunity of the algorithm against non-ideal cases such as measurement offset errors and phase unbalance is theoretically and experimentally verified. Being a model-independent fault analyzer, this method can be applied to all multiphase and single-phase motors.

  • 26.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1993Report (Other academic)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the lest-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 27.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1994In: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 2, p. 85-90Conference paper (Refereed)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the lest-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 28.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1994Report (Other academic)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the least-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 29.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1994In: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, Vol. 23, no 5, p. 329-338Article in journal (Refereed)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the least-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 30.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    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.
    On the Choice of Norms in System Identification1994In: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 2, p. 103-108Conference paper (Refereed)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 31.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    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.
    On the Choice of Norms in System Identification1994Report (Other academic)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 32.
    Akçay, Hüseyin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Håkan
    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.
    On the Choice of Norms in System Identification1996Report (Other academic)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 33.
    Akçay, Hüseyin
    et al.
    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.
    Hjalmarsson, Håkan
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On the Choice of Norms in System Identification1994Report (Other academic)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 34.
    Alami, Mohsen
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Interval Based Parameter Identification for System Biology2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This master thesis studies the problem of parameter identification for system biology. Two methods have been studied. The method of interval analysis uses subpaving as a class of objects to manipulate and store inner and outer approximations of compact sets. This method works well with the model given as a system of differential equations, but has its limitations, since the analytical expression for the solution to the ODE is not always obtainable, which is needed for constructing the inclusion function. The other method, studied, is SDP-relaxation of a nonlinear and non-convex feasibility problem. This method, implemented in the toolbox bio.SDP, works with system of difference equations, obtained using the Euler discretization method. The discretization method is not exact, raising the need of bounding this discretization error. Several methods for bounding this error has been studied. The method of ∞-norm optimization, also called worst-case-∞-norm is applied on the one-step error estimation method.

    The methods have been illustrated solving two system biological problems and the resulting SCP have been compared.

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  • 35.
    Albertos, Pedro
    et al.
    Polytechnical University of Valencia, Spain.
    Goodwin, Graham C.
    University of Newcastle, Australia.
    Isaksson, Alf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Pseudo Linear Regression Algorithm for On-Line Parameter Estimation with Missing Data1992Report (Other academic)
  • 36. Order onlineBuy this publication >>
    Albrektsson, Jörgen
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Optimisation of Off-Road Transport Missions2018Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Mines, construction sites, road construction and quarries are examples of applications where construction equipment are used. In a production chain consisting of several construction machines working together, the work needs to be optimised and coordinated to achieve an environmental friendly, energy efficient and productive production. Recent rapid development within positioning services, telematics and human machine interfaces (HMI) opens up for control of individual machines and optimisation of transport missions where several construction machines co-operate.

    The production chain on a work site can be split up in different sub-tasks of which some can be transport missions. Taking off in a transport mission where one wheel loader ("loader" hereinafter) and two articulated haulers ("haulers" hereinafter) co-operate to transport material at a set production rate [ton/h], a method for fuel optimal control is developed. On the mission level, optimal cycle times for individual sub-tasks such as wheel loader loading, hauler transport and hauler return, are established through the usage of Pareto fronts.

    The haulers Pareto fronts are built through the development of a Dynamic Programming (DP) algorithm that trades fuel consumption versus cycle time for a road stretch by means of a time penalty constant. Through varying the time penalty constant n number of times, discrete fuel consumption - cycle time values can be achieved, forming the Pareto front. At a later stage, the same DP algorithm is used to generate fuel optimal vehicle speed and gear trajectories that are used as control signals for the haulers. Input to the DP algorithm is the distance to be travelled, road inclination, rolling resistance coefficient and a max speed limit to avoid unrealistic optimisation results.

    Thus, a method to describe the road and detect the road related data is needed to enable the optimisation. A map module is built utilising an extended Kalman Filter, Rauch-Tung-Striebel smoother and sensor fusion to merge data and estimate parameters not observable by sensors. The map module uses a model of the vehicle, sensor signals from a GPS or GNSS sensor and machine sensors to establish a map of the road.

    The wheel loader Pareto front is based on data developed in previous research combined with Volvo in-house data. The developed optimisation algorithms are implemented on a PC and in an interactive computer tablet based system. A human machine interface is created for the tablet, guiding the operators to follow the optimal control signals, which is speed for the haulers and cycle time for the loader. To evaluate the performance of the system it is tested in real working conditions.

    The contributions develop algorithms, set up a demo mission control system and carry out experiments. Altogether rendering in a platform that can be used as a base for a future design of an off-road transport mission control system.

    List of papers
    1. Road estimation and fuel optimal control of an off-road vehicle
    Open this publication in new window or tab >>Road estimation and fuel optimal control of an off-road vehicle
    2017 (English)In: Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems, SciTePress, 2017, p. 58-67Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    SciTePress, 2017
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-142731 (URN)10.5220/0006247200580067 (DOI)000671783900005 ()978-989-758-242-4 (ISBN)
    Conference
    3rd International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2017, April 22-24, 2017, in Porto, Portugal
    Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2024-02-01
    2. Fuel Optimal Control of an Articulated Hauler Utilising a Human Machine Interface
    Open this publication in new window or tab >>Fuel Optimal Control of an Articulated Hauler Utilising a Human Machine Interface
    2019 (English)In: Smart Cities, Green Technologies, and Intelligent Transport Systems / [ed] Donnellan, Brian; Klein, Cornel; Helfert, Markus; Gusikhin, Oleg; Pascoal, António, Springer International Publishing , 2019, p. 190-208Conference paper, Published paper (Refereed)
    Abstract [en]

    Utilising optimal control presents an opportunity to increase the fuel efficiency in an off-road transport mission conducted by an articulated hauler. A human machine interface (HMI) instructing the hauler operator to follow the fuel optimal vehicle speed trajectory has been developed and tested in real working conditions. The HMI implementation includes a Dynamic Programming based method to calculate the optimal vehicle speed and gear shift trajectories. Input to the optimisation algorithm is road related data such as distance, road inclination and rolling resistance. The road related data is estimated in a map module utilising an Extended Kalman Filter (EKF), a Rauch-Tung-Striebel smoother and a data fusion algorithm. Two test modes were compared: (1) The hauler operator tried to follow the optimal vehicle speed trajectory as presented in the HMI and (2) the operator was given a constant target speed to follow. The objective of the second test mode is to achieve an approximately equal cycle time as for the optimally controlled transport mission, hence, with similar productivity. A small fuel efficiency improvement was found when the human machine interface was used.

    Place, publisher, year, edition, pages
    Springer International Publishing, 2019
    Series
    Communications in Computer and Information Science book series (CCIS), ISSN 1865-0929, E-ISSN 1865-0937 ; 921
    Keywords
    Off-road, Construction equipment, Human machine interface, Optimal control, Dynamic programming, Kalman filters
    National Category
    Vehicle Engineering
    Identifiers
    urn:nbn:se:liu:diva-153311 (URN)10.1007/978-3-030-02907-4_10 (DOI)000590141300010 ()978-3-030-02906-7 (ISBN)978-3-030-02907-4 (ISBN)
    Conference
    6th International Conference, SMARTGREENS 2017 and Third International Conference, VEHITS 2017, Porto, Portugal, April 22–24, 2017
    Note

    Funding agencies: Volvo CE; FFI - Strategic Vehicle Research and Innovation

    Available from: 2018-12-12 Created: 2018-12-12 Last updated: 2020-12-07
    3. Fuel optimal control of an off-road transport mission
    Open this publication in new window or tab >>Fuel optimal control of an off-road transport mission
    2018 (English)In: 2018 IEEE International Conference on Industrial Technology (ICIT), 2018, p. 175-180Conference paper, Published paper (Refereed)
    Abstract [en]

    To coordinate and optimise an off-road transport mission, on which a wheel loader and two articulated haulers cooperate, a fuel-optimal control algorithm is developed. The control algorithm utilises Pareto fronts of fuel consumption versus cycle time to e

    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-151856 (URN)10.1109/ICIT.2018.8352172 (DOI)000494652000027 ()978-1-5090-5949-2 (ISBN)
    Conference
    2018 IEEE International Conference on Industrial Technology (ICIT), 19-22 Feb.,Lyon, France
    Note

    Funding agencies:  Volvo CE; FFI - Strategic Vehicle Research and Innovation

    Available from: 2018-10-06 Created: 2018-10-06 Last updated: 2020-01-09
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  • 37.
    Albrektsson, Jörgen
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Road estimation and fuel optimal control of an off-road vehicle2017In: Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems, SciTePress, 2017, p. 58-67Conference paper (Refereed)
  • 38.
    Alegret, Guillem
    et al.
    MAN Diesel & Turbo, Copenhagen, Denmark.
    Llamas, Xavier
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Vejlgaard-Laursen, Morten
    MAN Diesel & Turbo, Copenhagen, Denmark.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Modeling of a Large Marine Two-Stroke Diesel Engine with Cylinder Bypass Valve and EGR System2015In: 10th IFAC Conference on Manoeuvring and Control of Marine Craft MCMC 2015: Copenhagen, 24–26 August 2015 / [ed] Roberto Galeazzi and Mogens Blanke, IFAC Papers Online, 2015, Vol. 48, p. 273-278Conference paper (Refereed)
    Abstract [en]

    A nonlinear mean value engine model (MVEM) of a two-stroke turbocharged marine diesel engine is developed, parameterized and validated against measurement data. The goal is to have a computationally fast and accurate engine model that captures the main dynamics and can be used in the development of control systems for the newly introduced EGR system. The tuning procedure used is explained, and the result is a six-state MVEM with seven control inputs that capture the main system dynamics.

    Download full text (pdf)
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  • 39.
    Algethami, Abdullah
    et al.
    Taif Univ, Saudi Arabia.
    Sarkar, Rajasree
    Indian Inst Technol Delhi, India.
    Amrr, Syed
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Banerjee, Arunava
    Univ Alberta, Canada.
    Bio-mimetic Autonomous Underwater Vehicle Control Using Time Delayed Estimation Technique2023In: 2023 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, AIM, IEEE , 2023, p. 930-935Conference paper (Refereed)
    Abstract [en]

    An autonomous underwater vehicle (AUV) is a crewless robotic vehicle that dives into the water and performs without human assistance. This paper focuses on developing trajectory tracking control for bio-mimetic AUV system under uncertain environments. Therefore, a relatively new control technique called time delay-based estimation control is proposed for trajectory tracking under multiple uncertainties. This algorithm estimates the total disturbance in the system using immediate past information of input and output of feedback state and control variables. The benefit of this scheme is that it avoids assumptions about a priori upper bound information of disturbance. Further, the control structure is simple and does not require any high-frequency switching or high gain to nullify the effects of disturbance. The theoretical analysis of the proposed scheme guarantees the uniformly ultimate bounded stability of the closed-loop system. The numerical analysis is also carried out to validate the control performance of the given algorithm for lemniscate reference path tracking.

  • 40.
    Ali Abdul-Amir, Ahmed
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Att lösa reglertekniska problem med Modelica2008Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Modelica is a multi-domain and equation-based modeling language. Modelica is based on object-oriented principles and non-causal modeling. The language is constructed to facilitate reuse and decompose models. The models and the modellibrary can modified to design a new nonlinear components.

    Object-oriented modeling is an excellent way to analyze and study large complex heterogeneous physical systems. The object-oriented modeling approach build on reusing and decomposition of models and non-causal modeling.

    Modeling physical systems often leads to a DAE system with index 2 or 3. It is required to use automated symbolic manipulation of the DAE system to do the simulation.

    Modelica need a compiler tool to run the simulation. Dymola is the dominating tool on the market. Through a graphic editor the user can easily model and simulate the physical system.

    Download full text (pdf)
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  • 41.
    Alickovic, Emina
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Kevric, Jasmin
    Int Burch University, Bosnia and Herceg.
    Subasi, Abdulhamit
    Effat University, Saudi Arabia.
    Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction2018In: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 39, p. 94-102Article in journal (Refereed)
    Abstract [en]

    This study proposes a new model which is fully specified for automated seizure onset detection and seizure onset prediction based on electroencephalography (EEG) measurements. We processed two archetypal EEG databases, Freiburg (intracranial EEG) and CHB-MIT (scalp EEG), to find if our model could outperform the state-of-the art models. Four key components define our model: (1) multiscale principal component analysis for EEG de-noising, (2) EEG signal decomposition using either empirical mode decomposition, discrete wavelet transform or wavelet packet decomposition, (3) statistical measures to extract relevant features, (4) machine learning algorithms. Our model achieved overall accuracy of 100% in ictal vs. inter-ictal EEG for both databases. In seizure onset prediction, it could discriminate between inter-ictal, pre-ictal, and ictal EEG with the accuracy of 99.77%, and between inter-ictal and pre-ictal EEG states with the accuracy of 99.70%. The proposed model is general and should prove applicable to other classification tasks including detection and prediction regarding bio-signals such as EMG and ECG. (C) 2017 Elsevier Ltd. All rights reserved.

  • 42.
    Alickovic, Emina
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Lunner, Thomas
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Eriksholm Research Centre, Oticon A/S, 20 Rortangvej, Snekkersten, Denmark.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    A System Identification Approach to Determining Listening Attention from EEG Signals2016In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE , 2016, p. 31-35Conference paper (Refereed)
    Abstract [en]

    We still have very little knowledge about how ourbrains decouple different sound sources, which is known assolving the cocktail party problem. Several approaches; includingERP, time-frequency analysis and, more recently, regression andstimulus reconstruction approaches; have been suggested forsolving this problem. In this work, we study the problem ofcorrelating of EEG signals to different sets of sound sources withthe goal of identifying the single source to which the listener isattending. Here, we propose a method for finding the number ofparameters needed in a regression model to avoid overlearning,which is necessary for determining the attended sound sourcewith high confidence in order to solve the cocktail party problem.

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  • 43.
    Aljanaideh, Khaled F.
    et al.
    MathWorks, MA 01760 USA.
    Bhattacharjee, Debraj
    MathWorks, MA 01760 USA.
    Singh, Rajiv
    MathWorks, MA 01760 USA.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    New Features in the System Identification Toolbox - Rapprochements with Machine Learning2021In: IFAC PAPERSONLINE, ELSEVIER , 2021, Vol. 54, no 7, p. 369-373Conference paper (Refereed)
    Abstract [en]

    The R2021b release of the System Identification ToolboxTM for MATLAB contains new features that enable the use of machine learning techniques for nonlinear system identification. With this release it is possible to build nonlinear ARX models with regression tree ensemble and Gaussian process regression mapping functions. The release contains several other enhancements including, but not limited to, (a) online state estimation using the extended Kalman filter and the unscented Kalman filter with code generation capability; (b) improved handling of initial conditions for transfer functions and polynomial models; (c) a new architecture of nonlinear black-box models that streamlines regressor handling, reduces memory footprint and improves numerical accuracy; and (d) easy incorporation of identification apps in teaching tools and interactive examples by leveraging the Live Editor tasks of MATLAB. Copyright (C) 2021 The Authors.

  • 44.
    Alkelin, Viktor
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Christiansen, Casper
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Alternative Input Devices for Steer-by-Wire Systems2020Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the recent push towards autonomous cars, a traditional steering wheel with its mechanical connection between the road and driver may soon be unnecessary. To facilitate interior design and lower production costs whilst still maintaining a manual alternative for maneuvering, an alternative steering input device relying on Steer-by-Wire technology is investigated.

    In order to finish the investigation and development of the steering device within the time-span of a master thesis, the limitation to only investigate the design of a hand wheel was established.

    The finished alternative steering device utilises an optical encoder for position measurement and a brushless direct current (DC) motor with a planetary gearbox for force feedback. Open-loop speed control proved to be insufficient with the available hardware. Instead, an approach of two PD-controllers regulating the angular error between the steering rack and the steering device was implemented successfully.

    Initially, mathematical models of the system components were derived and implemented in Mathworks Simulink. The transition from models to test rig implementation proved to be difficult due to unknown parameters in the hardware components such as embedded controllers in the steering gear and the internal works of the sensor emulator used to control the steering gear. By modifying parameters in accordance with system identification measurements performed on the test rig, the models could be validated.

    At the end of the project, a Volvo S60 was made available and the steering device was tested with real world driving. It was discovered that controllers tuned only for good reference following in the test rig did not translate to good driveability as the controller allowed for overly aggressive maneuvers. Following some in vehicle tuning, the proposed solution performed well during testing with surprisingly high drive-ability.

    For future iterations of similar hand wheel design projects, a user study was performed with regards to user experience, hand wheel size and perceived driveability.

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  • 45.
    Alkeryd, Martin
    Linköping University, Department of Electrical Engineering.
    Evaluation of Position Sensing Techniques for an Unmanned Aerial Vehicle2006Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
    Abstract [en]

    The use of Unmanned Aerial Vehicles (UAVs) has rapidly increased over the last years. This has been possible mainly due to the increased computing power of microcontrollers and computers. An UAV can be used in both civilian and military areas, for example surveillance and intelligence. The UAV concerned in this master's thesis is a prototype and is currently being developed at DST Control AB in Linköping.

    With the use of UAVs, the need for a positioning and navigation system arises. Inertial sensors can often give a good position estimation, however, they need continuous calibration due to error build-up and drift in gyros. An external reference is needed to correct for this drift and other errors. The positioning system investigated in this master's thesis is supposed to work in an area defined by an inverted cone with the height of 25m and a diameter of 10m.

    A comparison of different techniques suitable for position sensing has been performed. These techniques include the following: a radio method based on the Instrument Landing System (ILS), an optical method using a Position Sensing Detector (PSD), an optical method using the Indoor GPS system, a distance measurement method with ultrasound and also a discussion of the Global Positioning System (GPS).

    An evaluation system has been built using the PSD sensor and tests have been performed to evaluate its possibilities for positioning. Accuracy in the order of a few millimetres has been achieved in position estimation with the evaluation system.

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  • 46.
    Allansson, Niklas
    et al.
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems.
    Böhlin, Erik
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems.
    Multi Purpose Electro-Hydraulic Converter for More Electrical Power: A Case Study of Using Electro-Hydraulic Energy Converters in a Fighter Aircraft Application2024Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The hydraulic system in a fighter aircraft is not fully utilised during large parts of the flight mission were more electrical power is needed. To better utilise the hydraulic power the current Auxiliary Hydraulic Pump (AHP) and the Emergency Hydraulic Pump (EHP) can be exchanged to an Electro Hydraulic Energy Converter (EHEC). The EHEC has the possibility to provide hydraulic power to the system, but also convert hydraulic power into electric power. The control for such a unit can be implemented in different ways.

    A literature study was performed to decide a suitable architecture for use in a fighter aircraft application. A simulation model representing the resulting architecture was created. The simulation model was successful in describing the basic behaviour of the hydraulic system, but lacks a realistic representation of hydraulic consumers. 

    Different control strategies were created and tested on the simulation model with several test scenarios based on real flight data from tests performed on the aircraft. The control strategies were compared and suitable candidates were presented based on their relative performance and compared with the current hydraulic system behaviour.

    An architecture consisting of a variable displacement pump with over-center capabilities combined with a permanent magnet synchronous machine (PMSM) was decided to be used. A PI-controller with a feedforward on consumer flow was the best performing controller for use in emergency operation of the EHEC. For the case when regenerating electrical power a PI-controller with load pressure feedback is desired initially during start up. When reaching steady state a PI-controller without load pressure feedback is then advantageous.

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  • 47. Order onlineBuy this publication >>
    Allström, Andreas
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Highway Traffic State Estimation and Short-term Prediction2016Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Traffic congestion is increasing in almost all large cities, leading to a number of negative effects such as pollution and delays. However, building new roads is not a feasible solution. Instead, the use of the existing road network has to be optimized, together with a shift towards more sustainable transport modes. In order to achieve this there are several challenges that needs to be addressed. One challenge is the ability to provide accurate information about the current and future traffic state. This information is an essential input to the traffic management center and can be used to influence the choices made by the travelers. Accurate information about the traffic state on highways, where the potential to manage and control the traffic in general is very high, would be of great significance for the traffic managers. It would help the traffic managers to take action before the system reaches congestion and limit the effects of it. At the same time, the collection of traffic data is slowly shifting from fixed sensors to more probe based data collection. This requires an adaptation and further development of the traditional traffic models in order for them to handle and take advantage of the characteristics of all types of data, not just data from the traditionally used fixed sensors.

    The objective of this thesis is to contribute to the development and implementation of a model for estimation and prediction of the current and future traffic state and to facilitate an adaptation of the model to the conditions of the highway in Stockholm. The model used is a version of the Cell Transmission Model (CTM-v) where the velocity is used as the state variable. Thus, together with an Ensemble Kalman Filter (EnKF) it can be used to fuse different types of point speed measurements. The model is developed to run in real-time for a large network. Furthermore, a two-stage process used to calibrate the model is implemented. The results from the calibration and validation show that once the model is calibrated, the estimated travel times corresponds well with the ground truth travel times collected from Bluetooth sensors.

    In order to produce accurate short-term predictions for various networks and conditions it is vital to combine different methods. We have implemented and evaluated a hybrid prediction approach that assimilates parametric and non-parametric short-term traffic state prediction. To predict mainline sensor data we use a neural network, while the CTM-v is ran forward in time in order to predict future traffic states. The results show that both the hybrid approach and the CTM-v prediction without the additional predicted mainline sensor data is superior to a naïve prediction method for longer prediction horizons.

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  • 48.
    Almgren, Erik
    Linköping University, Department of Electrical Engineering.
    Sensor Fusion for Enhanced Lane Departure Warning2006Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
    Abstract [en]

    A lane departure warning system relying exclusively on a camera has several shortcomings and tends to be sensitive to, e.g., bad weather and abrupt manoeuvres. To handle these situations, the system proposed in this thesis uses a dynamic model of the vehicle and integration of relative motion sensors to estimate the vehicle’s position on the road. The relative motion is measured using vision, inertial, and vehicle sensors. All these sensors types are affected by errors such as offset, drift and quantization. However the different sensors are sensitive to different types of errors, e.g., the camera system is rather poor at detecting rapid lateral movements, a type of situation which an inertial sensor practically never fails to detect. These kinds of complementary properties make sensor fusion interesting. The approach of this Master’s thesis is to use an already existing lane departure warning system as vision sensor in combination with an inertial measurement unit to produce a system that is robust and can achieve good warnings if an unintentional lane departure is about to occur. For the combination of sensor data, different sensor fusion models have been proposed and evaluated on experimental data. The models are based on a nonlinear model that is linearized so that a Kalman filter can be applied. Experiments show that the proposed solutions succeed at handling situations where a system relying solely on a camera would have problems. The results from the testing show that the original lane departure warning system, which is a single camera system, is outperformed by the suggested system.

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  • 49.
    Almqvist, Håkan
    Linköping University, Department of Electrical Engineering.
    Automatic bucket fill2009Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This report contains the first step towards a complete, fully autonomous, robust bucket fill regulator for a wheel loader working with gravel materials.

    The bucket fill procedure is the most critical part of the work cycle of a wheel loader. It is a task that has a long learning curve and also is weary, even for experienced drivers. The automation of it could therefore have a big impact on the cost effectiveness for wheel loaders and for the comfort of the drivers.

    In this report, a suggestion for the complete solution of an automatic bucket fill regulator is presented. A regulator prototype is also constructed with a Volvo L120F as the base. The scope for the prototype is limited to one type of gravel material and quite optimal conditions for the wheel loader, but the complete solution is kept in mind throughout the synthesis. The constructed regulator is prepared for expansion, but the implementation and field testing is limited to the scope.

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  • 50.
    Alsén, Victoria
    Linköping University, Department of Electrical Engineering, Automatic Control.
    GNSS Aided Inertial Human Body Motion Capture2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Human body motion capture systems based on inertial sensors (gyroscopes andaccelerometers) are able to track the relative motions in the body precisely, oftenwith the aid of supplementary sensors. The sensor measurements are combinedthrough a sensor fusion algorithm to create estimates of, among other parame-ters, position, velocity and orientation for each body segment. As this algorithmrequires integration of noisy measurements, some drift, especially in the positionestimate, is expected. Taking advantage of the knowledge about the tracked sub-ject, a human body, models have been developed that improve the estimates, butposition still displays drift over time.In this thesis, a GNSS receiver is added to the motion capture system to givea drift-free measurement of the position as well as a velocity measurement. Theinertial data and the GNSS data complements each other well, particularly interms of observability of global and relative motions. To enable the models of thehuman body at an early stage of the fusion of sensor data, an optimization basedmaximum a posteriori algorithm was used, which is also better suited for thenonlinear system tracked compared to the conventional method of using Kalmanfilters.One of the models that improves the position estimate greatly, without addingadditional sensing, is the contact detection, with which the velocity of a segmentis set to zero whenever it is considered stationary in comparison to the surround-ing environment, e.g. when a foot touches the ground. This thesis looks at botha scenario when this contact detection can be applied and a scenario where itcannot be applied, to see what possibilities an addition of GNSS sensor couldbring to the human body motion tracking case. The results display a notable im-provement in position, both with and without contact detection. Furthermore,the heading estimate is improved at a full-body scale and the solution makes theestimates depend less on acceleration bias estimation.These results show great potential for more accurate estimates outdoors andcould prove valuable for enabling motion tracking of scenarios where the contactdetection model cannot be used, such as e.g. biking.

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