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  • 1.
    Ho, Du
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Linder, Jonas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Hendeby, Gustaf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Mass estimation of a quadcopter using IMU data2017Inngår i: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), June 13-16, 2017, Miami, FL, USA, Institute of Electrical and Electronics Engineers (IEEE), 2017, s. 1260-1266Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, an approach to estimate the mass of a quadcopter using only inertial measurements and pilot commands is presented. For this purpose, a lateral dynamic model describing the relation between the roll rate and the lateral acceleration is formulated. Due to the quadcopter’s inherent instability, a controller is used to stabilize the system and the data is collected in closed loop. Under the effect of feedback and disturbances, the inertial measurements used as input and output are correlated with the disturbances, which complicates the parameter estimation. The parameters of the model are estimated using several methods. The simulation and experimental results show that the instrumental-variable method has the best potential to estimate the mass of the quadcopter in this setup.

  • 2.
    Ho, Du
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Linder, Jonas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Hendeby, Gustaf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Vertical modeling of a quadcopter for mass estimation and diagnosis purposes2017Inngår i: Proceedings of the Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this work, we estimate a model of the vertical dynamics of a quadcopter and explain how this model can be used for mass estimation and diagnosis of system changes. First, a standard thrust model describing the relation between the calculated control signals of the rotors and the thrust that is commonly used in literature is estimated. The estimation results are compared to those using a refined thrust model and it turns out that the refined model gives a significant improvement. The combination of a nonlinear model and closed-loop data poses some challenges and it is shown that an instrumental variables approach can be used to obtain accurate estimates. Furthermore, we show that the refined model opens up for fault detection of the quadcopter. More specifically, this model can be used for mass estimation and also for diagnosis of other parameters that might vary between and during missions.

  • 3.
    Jansson, Andreas
    et al.
    Statens väg- och transportforskningsinstitut, Fordonsteknik och simulering, FTS.
    Olsson, Erik
    Statens väg- och transportforskningsinstitut, Fordonsteknik och simulering, FTS.
    Linder, Jonas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjort, Mattias
    Statens väg- och transportforskningsinstitut, Fordonsteknik och simulering, FTS.
    Developing of a Driver Model for Vehicle Testing2014Inngår i: Proceedings of the 14th International Symposium on Advanced Vehicle Control (AVEC), Tokyo, September 2014, 2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    There is today no established automated method for testing vehicles or tyres, and the most common option is using professional drivers for this purpose. The tests are supposed to be fair and repeatable, which means using human drivers for these kinds of vehicle testing is not an option. Using a steering robot modelled to drive as a human is therefore preferable. The approach described in this paper shows how a driver model can be created by using a control algorithm based on gathered data from human drivers performing double lane change (DLC) manoeuvres in a simulator. The implemented controller shows how human drivers’ behaviors can be captured using control theory.

  • 4.
    Linder, Jonas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Graybox Modelling of Ships Using Indirect Input Measurements2014Licentiatavhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    A ship's roll dynamics is very sensitive to changes in the loading conditions and a worst-case scenario is that the ship will capsize. Actually, the mass and center of mass are two of the most influential parameters in most mechanical systems. However, it is difficult to uniquely estimate these parameters for a ship under normal operational conditions without special experiments or equipment.

    Instead of focusing on a sensor-rich environment where all possible signals on a ship can be measured and a complete model of the ship can be estimated, this thesis presents an approach where a model of a subsystem of the ship's dynamics is estimated using only a limited set of sensors. More specifically, the roll dynamics is studied and it is assumed that only motion measurements from an inertial measurement unit (IMU) together with measurements of the rudder angle are available. Hence, direct measurements of the true inputs to the subsystem are not available, but the measurements indirectly contain information about the inputs and these indirect input measurements can be used as a substitute.

    To understand the properties of the proposed method, it is applied to an approximate model of the ship's roll dynamics. The analyses show that only a subset of the unknown parameters can be estimated simultaneously and that the estimation problem is similar to closed-loop system identification.

    A multi-stage method that uses several datasets is introduced to circumvent the restrictions shown in the identifiability analysis. An iterative closed-loop instrumental variable approach is used to estimate subsets of the parameters in each step. The approach is verified on experimental data with good results.

    It is shown that a well-established and more complete ship model can be used to derive a generalization of the approximate model, with more input measurements and a few extra parameters. The generalized model has the same basic properties as the approximate model. The added complexity is due to the ship's interaction with water. Because of this extra complexity, an iterative joint closed-loop instrumental variable approach based on a graybox formulation and using multiple datasets simultaneously is introduced to estimate the parameters.

    Finally, experiments with a scale ship model are described. The joint identification method is applied to the collected data and gives promising results.

  • 5.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Identification and prediction in dynamic networks with unobservable nodes2016Rapport (Annet vitenskapelig)
    Abstract [en]

    The interest for system identification in dynamic networks has increased recently with a wide variety of applications. In many cases, it is intractable or undesirable to observe all nodes in a network and thus, to estimate the complete dynamics. If the complete dynamics is not desired, it might even be challenging to estimate a subset of the network if key nodes are unobservable due to correlation between the nodes. In this contribution, we will discuss an approach to treat this problem. The approach relies on additional measurements that are dependent on the unobservable nodes and thus indirectly contain information about them. These measurements are used to form an alternative indirect model that is only dependent on observed nodes. The purpose of estimating this indirect model can be either to recover information about modules in the original network or to make accurate predictions of variables in the network. Examples are provided for both recovery of the original modules and prediction of nodes.

  • 6.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On Indirect Input Measurements2015Rapport (Annet vitenskapelig)
    Abstract [en]

    A common issue with many system identification problems is that the true input to the system is unknown. In this paper, a framework, based on indirect input measurements, is proposed to solve the problem when the input is partially or fully unknown, and cannot be measured directly. The approach relies on measurements that indirectly contain information about the unknown input. The resulting indirect model formulation, with both direct- and indirect input measurements as inputs, can be used to estimate the desired model of the original system. Due to the similarities with closed-loop system identification, an iterative instrumental variable method is proposed to estimate the indirect model. To show the applicability of the proposed method, it is applied to data from an inverted pendulum experiment with good results.

  • 7.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    On Indirect Input Measurements2015Inngår i: Proceedings of the 17th IFAC Symposium on System Identification, 2015, s. 104-109Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A common issue with many system identification problems is that the true input to the system is unknown. In this paper, a framework, based on indirect input measurements, is proposed to solve the problem when the input is partially or fully unknown, and cannot be measured directly. The approach relies on measurements that indirectly contain information about the unknown input. The resulting indirect model formulation, with both direct and indirect input measurements as inputs, can be used to estimate the desired model of the original system. Due to the similarities with closed-loop system identification, an iterative instrumental variable method is proposed to estimate the indirect model. To show the applicability of the proposed method, it is applied to data from an inverted pendulum experiment with good results. 

  • 8.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Fossen, Thor I.
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Johansen, Tor Arne
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Modeling for IMU-based Online Estimation of a Ship's Mass and Center of Mass2015Rapport (Annet vitenskapelig)
    Abstract [en]

    A ship's roll dynamics is very sensitive to changes in the loading conditions and a worst-case scenario is the loss of stability.  This paper proposes an approach for online estimation of a ship's mass and center of mass. Instead of focusing on a sensor-rich environment where all possible signals on a ship can be measured and a complete model of the ship can be estimated, a minimal approach is adopted. A model of the roll dynamics is derived from a well-established model in literature and it is assumed that only motion measurements from an inertial measurement unit together with measurements of the rudder angle are available. Furthermore, identifiability properties and disturbance characteristics of the model are presented. Due to the properties of the model, the parameters are estimated with an iterative instrumental variable approach to mitigate the influence of the disturbances and it uses multiple datasets simultaneously to overcome identifiability issues. Finally, a simulation study is presented to investigate the sensitivity to the initial conditions and it is shown that there is a low sensitivity for the desired parameters.

  • 9.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Fossen, Thor I.
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Johansen, Tor Arne
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Modeling for IMU-based Online Estimation of a Ship's Mass and Center of Mass2015Inngår i: Proceedings of the 10th Conference on Manoeuvring and Control of Marine Craft, 2015, , s. 16Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A ship's roll dynamics is very sensitive to changes in the loading conditions and a worst-case scenario is the loss of stability.  This paper proposes an approach for online estimation of a ship's mass and center of mass. Instead of focusing on a sensor-rich environment where all possible signals on a ship can be measured and a complete model of the ship can be estimated, a minimal approach is adopted. A model of the roll dynamics is derived from a well-established model in literature and it is assumed that only motion measurements from an inertial measurement unit together with measurements of the rudder angle are available. Furthermore, identifiability properties and disturbance characteristics of the model are presented. Due to the properties of the model, the parameters are estimated with an iterative instrumental variable approach to mitigate the influence of the disturbances and it uses multiple datasets simultaneously to overcome identifiability issues. Finally, a simulation study is presented to investigate the sensitivity to the initial conditions and it is shown that the sensitivity is low for the desired parameters.

  • 10.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Fossen, Thor I.
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Johansen, Tor Arne
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Online Estimation of Ship's Mass and Center of Mass Using Inertial Measurements2015Rapport (Annet vitenskapelig)
    Abstract [en]

    A ship's roll dynamics is sensitive to the mass and mass distribution. Changes in these physical properties might introduce unpredictable behavior of the ship and a {worst-case} scenario is that the ship will capsize. In this paper, a recently proposed approach for online estimation of mass and center of mass is validated using experimental data. The experiments were performed using a scale model of a ship in a wave basin. The data was collected in free run experiments where the rudder angle was recorded and the ship's motion was measured using an inertial measurement unit. The motion measurements are used in conjunction with a model of the roll dynamics to estimate the desired properties. The estimator uses the rudder angle measurements together with an instrumental variable method to mitigate the influence of disturbances. The experimental study shows that the properties can be estimated with quite good accuracy but that variance and robustness properties can be improved further.

  • 11.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Fossen, Thor I.
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Johansen, Tor Arne
    Centre for Autonomous Marine Operations and Systems (AMOS), Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Online Estimation of Ship's Mass and Center of Mass Using Inertial Measurements2015Inngår i: Proceedings of the 10th Conference on Manoeuvring and Control of Marine Craft, 2015, , s. 16Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A ship's roll dynamics is sensitive to the mass and mass distribution. Changes in these physical properties might introduce unpredictable behavior of the ship and a worst-case scenario is that the ship will capsize. In this paper, a recently proposed approach for online estimation of mass and center of mass is validated using experimental data. The experiments were performed using a scale model of a ship in a wave basin. The data were collected in free run experiments where the rudder angle was recorded and the ship's motion was measured using an inertial measurement unit. The motion measurements are used in conjunction with a model of the roll dynamics to estimate the desired properties. The estimator uses the rudder angle measurements together with an instrumental variable method to mitigate the influence of disturbances. The experimental study shows that the properties can be estimated with quite good accuracy but that variance and robustness properties can be improved further.

  • 12.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Closed-loop Instrumental Variable Approach to Mass and Center of Mass Estimation Using IMU Data2014Inngår i: Proceedings of the 53rd Conference on Decision and Control, 2014, s. 283-289Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, an instrumental variable (IV) method for estimating the mass and center of mass (CM) of a ship using IMU data has been further investigated. Here, this IV method, which was proposed in an earlier paper, has been analyzed from a closed-loop point of view. This new perspective reveals the properties of the system and dependencies of the signals used in the estimation procedure. Due to similarities with closed-loop identification, previous results in the closed-loop identification field have been used as an inspiration to improve the IV estimator. Since the roll dynamics of a ship is well described by a pendulum model, a pendulum experiment has been carried out to validate the performance both of the original and the improved IV estimators. The experiments gave good results for the improved IV estimator with significantly lower variances and relative errors than the previous IV estimator.

  • 13.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Enqvist, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Sjöberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Identifiability of physical parameters in systems with limited sensors2014Inngår i: Proceedings of the 19th IFAC World Congress, 2014, s. 6454-6459Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, a method for estimating physical parameters using limited sensors is investigated. As a case study, measurements from an IMU are used for estimating the change in mass and the change in center of mass of a ship. The roll motion is studied and an instrumental variable method estimating the parameters of a transfer function from the tangential acceleration to the angular velocity is presented. It is shown that only a subset of the unknown parameters are identifiable simultaneously. A multi-stage identification approach is presented as a remedy for this. A limited simulation study is also presented to show the properties of the estimator. This shows that the method is indeed promising but that more work is needed to reduce the variance of the estimator.

  • 14.
    Linder, Jonas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Lindkvist, Simon
    Sjöberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Two-Step Framework for Interactive Multi-Objective Optimization2012Rapport (Annet vitenskapelig)
    Abstract [en]

    In many real-world optimization applications there are often a number of conflicting objective functions that are all important to optimize. The purpose of multiobjective optimization (MOO) is to give the decision maker(DM) an understanding of how these functions are conflicting and the possibility to choose an appropriate trade-off between them. There are multiple methods for solving MOO problems but the focus in this paper is on interactive methods. When the size and complexity of the MOO problem grows the time needed to find a solution is too long to yield a pleasant experience for the DM. In this paper, a method to replace the original MOO problem with an approximation is suggested to speed up the process. The approximation is created and used in a two-step framework which makes it possible to investigate the Pareto frontier in real-time and that can handle nonlinear and non-convex MOO problems with m objective functions. The first step generates a number of samples of the complete Pareto frontier which is sparse but dense enough for the approximation. The second stepis an interactive tool for the DM to use to continuously and in real-time navigate on the approximated Pareto set in both objective- and decision space. The tool is used to investigate the Pareto frontier and to find a preferred solution. A method of decomposing the approximated set into simplices has been developed using Delaunay triangulation. This methodis able to make a good approximation for sets that are non-convex. The method is also able to handle disconnected sets and holes. This makes it possible to change the feasible region in both decision- and objective space. The framework is demonstrated on three example problems that show the functionality and performance of the implemented framework.

  • 15.
    Sjöberg, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Lindkvist, Simon
    ABB, Sweden.
    Linder, Jonas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Daneryd, Anders
    ABB, Sweden.
    Interactive Multiobjective Optimization for the Hot Rolling Process2012Inngår i: Proceedings of 51st IEEE Conference on Decision and Control, 2012, s. 7030-7036Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, multi-objective optimization is applied to the hot rolling process. It is modeled mostly using first principle models considering, for instance, the mass balance (or mass flow rate), the tensions in the material, the power requirements, the thermal field, and the microstructure of the material.

    Two optimization formulations are considered. In the first case, both the grain size and the power consumption in the rolling process are minimized. It is shown that the result from a single-objective optimization formulation, i.e., where only one of the two objectives are considered, yields control schedules with poor performance for the other objective. Furthermore, the differences between optimal control schedules for different objectives are compared and analyzed. The second case is a design optimization problem where the optimal positioning of cooling pipes is considered. This study shows how the MOO framework can be used to systematically choose a good cooling pipe setup. 

    The two studies shows that MOO can be a helpful tool when designing and running hot rolling processes. Furthermore, navigation among the Pareto optimal solutions is very useful when the user wants to learn how the control variables interact with the process.

  • 16.
    Sjöberg, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Lindkvist, Simon
    ABB Corporate Research, Sweden.
    Linder, Jonas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Öhr, Jonas
    ABB Crane Systems, Sweden.
    Interactive Multiobjective Optimization for a Grab-Shift Unloader Crane2014Inngår i: Proceedings of the 19th IFAC World Congress, 2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, multiobjective optimization is applied to an optimal control problem for a grab-shift unloader crane. The crane is modeled as a cart-pendulum system with varying rope length and the trajectory of the grab is limited by the ship, the quay, and the crane structure. The objectives to minimize are chosen as time, energy and maximal instantaneous power. The optimal control problem is solved using a direct simultaneous optimal control method. The study shows that MOO can be an efficient tool when choosing a good compromise between conflicting objectives such as time and energy. Furthermore, navigation among the Pareto optimal solutions has proven to be very useful when a user wants to learn how the control variables interact with the process. 

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