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  • 151.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Time and Frequency Domain Convergence Properties in Iterative Learning Control2002In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 75, no 14, p. 1114-1126Article in journal (Refereed)
    Abstract [en]

    The convergence properties of iterative learning control (ILC) algorithms are considered. The analysis is carried out in a framework using linear iterative systems, which enables several results from the theory of linear systems to be applied. This makes it possible to analyse both first-order and high-order ILC algorithms in both the time and frequency domains. The time and frequency domain results can also be tied together in a clear way. Results are also given for the iteration-variant case, i.e. when the dynamics of the system to be controlled or the ILC algorithm itself changes from iteration to iteration.

  • 152.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Using Iterative Learning Control to get Better Performance of Robot Control Systems1997In: Proceedings of Robotikdagarna 1997, 1997Conference paper (Other academic)
    Abstract [en]

    Many manipulators at work in factories today repeat their motions over and over in cycles and if there are errors in following the trajectory these errors will also be repeated cycle after cycle. The basic idea behind iterative learning control (ILC) is that the controller should learn from previous cycles and perform better every cycle. Iterative learning control is used in combination with conventional feed-back and feed-forward control, and it is shown that learning control signal can handle the effects of unmodeled dynamics and friction. Convergence and disturbance effects as well as the choice of filters in the updating scheme are also addressed.

  • 153.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Using Iterative Learning Control to get Better Performance of Robot Control Systems1997Report (Other academic)
    Abstract [en]

    Many manipulators at work in factories today repeat their motions over and over in cycles and if there are errors in following the trajectory these errors will also be repeated cycle after cycle. The basic idea behind iterative learning control (ILC) is that the controller should learn from previous cycles and perform better every cycle. Iterative learning control is used in combination with conventional feed-back and feed-forward control, and it is shown that learning control signal can handle the effects of unmodeled dynamics and friction. Convergence and disturbance effects as well as the choice of filters in the updating scheme are also addressed.

  • 154.
    Samuelsson, Andreas
    et al.
    ABB Corporate Research, Västerås, Sweden.
    Carvalho Bittencourt, André
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Saarinen, Kari
    ABB Corporate Research, Västerås, Sweden.
    Sander Tavallaey, Shiva
    ABB Corporate Research, Västerås, Sweden.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. ABB Robotics, Västerås, Sweden.
    Andersson, Hans
    ABB Robotics, Västerås, Sweden.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Simulation based Evaluation of Fault Detection Algorithms: Applications to Wear Diagnosis in Manipulators2014In: Proceedings of the 19th IFAC World Congress, 2014Conference paper (Refereed)
    Abstract [en]

    Fault detection algorithms (FDAs) process data to generate a test quantity. Test quantities are used to determine presence of a fault in a monitored system, despite disturbances. Because only limited knowledge of the system can be embedded in an FDA, it is important to evaluate it in scenarios relevant in practice. In this paper, simulation based approaches are proposed in an attempt to determine: i) which disturbances affect the output of an FDA the most; ii) how to compare the performance of dierent FDAs; and iii) which combinations of fault change size and disturbances variations are allowed to achieve satisfactory performance. The ideas presented are inspired by the literature of design of experiments, surrogate models, sensitivity analysis and change detection. The approaches are illustrated for the problem of wear diagnosis in manipulators where three FDAs are considered. The application study reveals that disturbances caused by variations in temperature and payload mass error affect the FDAs the most. It is also shown how the size of these disturbances delimit the capacity of an FDA to relate to wear changes. Further comparison of the FDAs reveal which performs "best" in average.

  • 155.
    Svensson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Design-Build-Test course in electronics based on the CDIO framework for engineering education2012In: International Journal of Electrical Engineering Education, ISSN 0020-7209, E-ISSN 2050-4578, Vol. 49, no 4, p. 349-364Article in journal (Refereed)
    Abstract [en]

    A Design-Build-Test (DBT) course in electronics is presented. The course is designed based on the CDIO (Conceive-Design-Implement-Operate) framework for engineering education. It is part of the curriculum of two engineering programs at Linköping University, Sweden, where it has been given successfully for a number of years. The cornerstones of the course consist of carefully designed learning outcomes based on the CDIO Syllabus, a structured project management model such that the project tasks are carried out according to professional and industry-like routines, with well-designed organisation of the staff supporting the course, and challenging project tasks.

  • 156.
    Svensson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Teaching Project Courses in Large Scale Using Industry Like Methods - Experiences After Ten Years2012Conference paper (Other academic)
    Abstract [en]

    A Design-Build-Test (DBT) project course in electronics is presented. The course was developed during the first years of the CDIO Initiative, and it has been given successfully for almost ten years within two engineering programs at Linköping University. More than 2000 students have passed the course, and it is considered to be one of the most popular and also demanding courses within these programs. The key factors that have contributed to the success of the course are:

    • Clearly defined learning outcomes.
    • A suitable and well working course organization.
    • A systematic method for project management.
    • Challenging project tasks of sufficient complexity.
    • Laboratory workspaces with modern equipment and high availability.

    The aim of the paper is to describe these key factors in more detail based on the experiences that have been gained during the almost ten years the course has been given.

  • 157.
    Wahlberg, Bo
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Some Asymptotic Results in Recursive Identification using Laguerre Models1990In: Proceedings of the 29th IEEE Conference on Decision and Control, 1990, p. 1069-1073 vol.2Conference paper (Refereed)
    Abstract [en]

    Frequency domain expressions for the quality of recursively identified Laguerre models are presented. These models generalize finite impulse response models by using a priori information about the dominating time constants of the system to be identified. Expressions for the model quality are derived under the assumptions that the system varies slowly, that the model is updated slowly, and that the model order is high. The model quality is evaluated by investigating the properties of the estimated transfer function, and explicit expressions for the mean square error of the transfer function estimate are derived.

  • 158.
    Wallen Axehill, Johanna
    et al.
    Saab Aeronaut, SE-58188 Linkoping, Sweden.
    Dressler, Isolde
    Lund University, Sweden.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Robertsson, Anders
    Lund University, Sweden.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation-based ILC applied to a parallel kinematic robot2014In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 33Article in journal (Refereed)
    Abstract [en]

    Estimation-based iterative learning control (ILC) is applied to a parallel kinematic manipulator known as the Gantry-Tau parallel robot. The system represents a control problem where measurements of the controlled variables are not available. The main idea is to use estimates of the controlled variables in the ILC algorithm, and in the paper this approach is evaluated experimentally on the Gantry-Tau robot. The experimental results show that an ILC algorithm using estimates of the tool position gives a considerable improvement of the control performance. The tool position estimate is obtained by fusing measurements of the actuator angular positions with measurements of the tool path acceleration using a complementary filter.

  • 159.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Dressler, Isolde
    Lund University, Sweden.
    Robertsson, Anders
    Lund University, Sweden.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Observer-based ILC Applied to the Gantry-Tau Parallel Kinematic Robot2011In: Proceedings of the 18th IFAC World Congress, IFAC , 2011, p. 992-998Conference paper (Refereed)
    Abstract [en]

    Three approaches of iterative learning control (ILC) applied to a Gantry-Tau parallel kinematic robot are studied; ILC algorithms using 1) measured motor angles, 2) tool-position estimates, and for evaluation purposes, 3) measured tool position. The approaches are compared experimentally, with the tool performance evaluated using external sensors. It is concluded that the tool performance can be improved using tool-position estimates in the ILC algorithm, compared to when using motor-angle measurements. Applying ILC algorithms to a system following trajectories with so-called lead-in/lead-out is also considered in the paper.

  • 160.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Dressler, Isolde
    Lund University, Sweden.
    Robertsson, Anders
    Lund University, Sweden.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Observer-Based ILC Applied to the Gantry-Tau Parallel Kinematic Robot: Modelling, Design and Experiments2010Report (Other academic)
    Abstract [en]

    Three different approaches of iterative learning control (ILC) applied to a parallel kinematic robot are studied. First, the ILC algorithm is based on measured motor angles only. Second, tool-position estimates are used in the ILC algorithm. For evaluation, the ILC algorithm finally is based on measured tool position. Model-based tuning of the ILC filters enables learning above the resonance frequencies of the system. The approaches are compared experimentally on a Gantry-Tau prototype, with the tool performance being evaluated by using external sensors. It is concluded that the tool performance can be improved by using tool-position estimates in the ILC algorithm, compared to when using motor-angle measurements. In the paper applying ILC algorithms to a system following trajectories with so-called lead-in/lead-out is also considered, as well as dynamic modelling of the Gantry-Tau prototype.

  • 161.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Henriksson, Robert
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Moberg, Stig
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates2009Report (Other academic)
    Abstract [en]

    Estimates from an extended Kalman filter (EKF) is used in an Iterative Learning Control (ILC) algorithm applied to a realistic two-link robot model with flexible joints. The angles seen from the arm side of the joints (arm angles) are estimated by an EKF in two ways: 1) using  measurements of angles seen from the motor side of the joints (motor angles), which normally  are the only measurements available in commercial industrial robot systems, 2) using both motor- angle and tool-acceleration measurements. The estimates are then used in an ILC algorithm. The results show that the actual arm angles are clearly improved compared to when only motor angles are used in the ILC update, even though model errors are introduced.

  • 162.
    Wallén, Johanna
    et al.
    Combitech AB, Linköping, Sweden.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Analysis of boundary effects in iterative learning control2013In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 86, no 3, p. 410-415Article in journal (Refereed)
    Abstract [en]

    Boundary effects in iterative learning control (ILC) algorithms are considered in this article. ILC algorithms involve filtering of input and error signals over finite-time intervals, often using non-causal filters, and it is important that the boundary effects of the filtering operations are handled in an appropriate way. The topic is studied using both a proposed theoretical framework and simulations, and it is shown that the method for handling the boundary effects has impact on the stability and convergence properties of the ILC algorithm.

  • 163.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Derivation of Kinematic Relations for a Robot using Maple2006In: Proceedings of Reglermöte 2006, 2006Conference paper (Other academic)
    Abstract [en]

    A first step towards making a toolbox in Maple for industrial robot modelling is taken. Position and orientation of the tool can be determined in terms of the Denavit-Hartenberg joint variables and also the Jacobian relating the linear and angular velocities to the joint velocities. Further on it will be possible to, eg, differentiate the Jacobian. Future work includes to evaluate different kinds of sensors and sensor locations and symbolically generate the kinematic models using Maple. It also means to incorporate the models in Matlab- or C-code for including the results, eg, in an Extended Kalman Filter algorithm for state estimation.

  • 164.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Derivation of Kinematic Relations for a Robot using Maple2006Report (Other academic)
    Abstract [en]

    A first step towards making a toolbox in Maple for industrial robot modelling is taken. Position and orientation of the tool can be determined in terms of the Denavit-Hartenberg joint variables and also the Jacobian relating the linear and angular velocities to the joint velocities. Further on it will be possible to, eg, differentiate the Jacobian. Future work includes to evaluate different kinds of sensors and sensor locations and symbolically generate the kinematic models using Maple. It also means to incorporate the models in Matlab- or C-code for including the results, eg, in an Extended Kalman Filter algorithm for state estimation.

  • 165.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Some Implementation Aspects of Iterative Learning Control2010Report (Other academic)
    Abstract [en]

    Some implementation aspects of Iterative Learning Control (ILC) are considered. Since the ILC algorithm involves filtering of various signals over finite time intervals, often using non-causal filters, it is important that the boundary effects of the filtering operations are handled in an appropriate way when implementing the ILC algorithm. The paper illustrates in both theoretical analysis using the matrix description and in simulations of a twomass system that the method of implementation for handling the boundary effects can have large influence over stability and convergence properties of the ILC algorithm.

  • 166.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Henriksson, Robert
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Moberg, Stig
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates2009In: Proceedings of 48th IEEE Conference on Decision and Control, IEEE , 2009, p. 458-463Conference paper (Refereed)
    Abstract [en]

    Estimates from an extended Kalman filter (EKF) is used in an Iterative Learning Control (ILC) algorithm applied to a realistic two-link robot model with flexible joints. The angles seen from the arm side of the joints (arm angles) are estimated by an EKF in two ways: 1) using  measurements of angles seen from the motor side of the joints (motor angles), which normally  are the only measurements available in commercial industrial robot systems, 2) using both motor- angle and tool-acceleration measurements. The estimates are then used in an ILC algorithm. The results show that the actual arm angles are clearly improved compared to when only motor angles are used in the ILC update, even though model errors are introduced.

  • 167.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2010In: Proceedings of Reglermöte 2010, 2010Conference paper (Other academic)
    Abstract [en]

    A framework for Iterative Learning Control (ILC) is derived when the ILC algorithm is based on estimates from an observer. Under the assumption that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is then discussed when the ILC algorithm is based on different errors and it is exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

  • 168.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2009In: Proceedings of Symposium on Learning Control at IEEE CDC, 2009Conference paper (Refereed)
    Abstract [en]

    A framework for Iterative Learning Control (ILC) is proposed for the situation when the ILC algorithm is based on an estimate of the controlled variable obtained from an observer-based estimation procedure. Under the assumption that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is then exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

  • 169.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2009Report (Other academic)
    Abstract [en]

    A framework for Iterative Learning Control (ILC) is proposed for the situation when the ILC algorithm is based on an estimate of the controlled variable obtained from an observer-based estimation procedure. Under the assumption that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is then exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

  • 170.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2011In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 13, no 1, p. 3-14Article in journal (Refereed)
    Abstract [en]

    A framework for iterative learning control (ILC) is proposed for the situation when an ILC algorithm uses an estimate of the controlled variable obtained from an observer-based estimation procedure. Assuming that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

  • 171.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Accelerometer Based Evaluation of Industrial Robot Kinematics Derived in Maple2007In: Proceedings of Mekatronikmöte 2007, 2007Conference paper (Other academic)
    Abstract [en]

    In this paper a step toward making a toolbox for industrial robot modelling based on the computer algebra tool Maple is taken. It can be seen as a modelling platform for efficient derivation of the necessary equations for doing, eg, sensor fusion or state estimation by an Extended Kalman Filter (EKF) algorithm. Forward kinematics is studied and the position and orientation of the robot tool are determined in terms of the Denavit-Hartenberg joint variables. Linear and angular velocities and accelerations are derived using the Jacobian. The toolbox is exemplified using an IRB1400 from ABB Robotics with a so called parallelogram linkage structure. The kinematic relations received are verified using the robot IRB1400 with an accelerometer placed on the robot tool and it is shown that measured acceleration and theoretical acceleration derived from the kinematics agree well. However no flexibilities in the modelling are taken into account, which results in differences between measured and derived acceleration when several motors of the robot cooperate in the motion.

  • 172.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Accelerometer Based Evaluation of Industrial Robot Kinematics Derived in Maple2007Report (Other academic)
    Abstract [en]

    In this paper a step toward making a toolbox for industrial robot modelling based on the computer algebra tool Maple is taken. It can be seen as a modelling platform for efficient derivation of the necessary equations for doing, eg, sensor fusion or state estimation by an Extended Kalman Filter (EKF) algorithm. Forward kinematics is studied and the position and orientation of the robot tool are determined in terms of the Denavit-Hartenberg joint variables. Linear and angular velocities and accelerations are derived using the Jacobian. The toolbox is exemplified using an IRB1400 from ABB Robotics with a so called parallelogram linkage structure. The kinematic relations received are verified using the robot IRB1400 with an accelerometer placed on the robot tool and it is shown that measured acceleration and theoretical acceleration derived from the kinematics agree well. However no flexibilities in the modelling are taken into account, which results in differences between measured and derived acceleration when several motors of the robot cooperate in the motion.

  • 173.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Arm-Side Evaluation of ILC Applied to a Six-Degrees-of-Freedom Industrial Robot2008In: Proceedings of the 17th IFAC World Congress, 2008, , p. 13450-13455p. 13450-13455Conference paper (Refereed)
    Abstract [en]

    Experimental results from a first-order ILC algorithm applied to a large-size sixdegrees-of-freedom commercial industrial robot are presented. The ILC algorithm is based on measurements of the motor angles, but in addition to the conventional evaluation of the ILC algorithm based on the motor-side error, the tool-path error on the arm side is evaluated using a laser-measurement system. Experiments have been carried out in three operating points using movements that represent typical paths in a laser-cutting application and different choices of algorithm design parameters have been studied. The motor-angle error is reduced substantially in all experiments and the tool-path error is reduced in most of the cases. In one operating point, however, the error does not decrease as much and an oscillatory tool behaviour is observed. Changed filter variables can give worse error reduction in all operating points. To achieve even better performance, especially in difficult operating points, it is concluded that an arm-side measurement, from for example an accelerometer, needs to be included in the learning.

  • 174.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Arm-Side Evaluation of ILC Applied to a Six-Degrees-of-Freedom Industrial Robot2007Report (Other academic)
    Abstract [en]

    Experimental results from a first-order ILC algorithm applied to a large-size sixdegrees-of-freedom commercial industrial robot are presented. The ILC algorithm is based on measurements of the motor angles, but in addition to the conventional evaluation of the ILC algorithm based on the motor-side error, the tool-path error on the arm side is evaluated using a laser-measurement system. Experiments have been carried out in three operating points using movements that represent typical paths in a laser-cutting application and different choices of algorithm design parameters have been studied. The motor-angle error is reduced substantially in all experiments and the tool-path error is reduced in most of the cases. In one operating point, however, the error does not decrease as much and an oscillatory tool behaviour is observed. Changed filter variables can give worse error reduction in all operating points. To achieve even better performance, especially in difficult operating points, it is concluded that an arm-side measurement, from for example an accelerometer, needs to be included in the learning.

  • 175.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Comparison of Performance and Robustness for two Classical ILC Algorithms Applied to a Flexible System2008Report (Other academic)
    Abstract [en]

    When an ILC algorithm is applied to an industrial robot, the goal is to move the tool along a desired trajectory, while only the motor position canbe measured. In this paper aspects of robustness and performance are discussed when an ILC algorithm is applied to a flexible two-mass system. It is shown that the stabilising controller of the two-mass system also directly affects the robustness properties of the ILC algorithm. A classical noncausa lP-ILC algorithm and a model-based ILC design using optimisation are applied to the system, based on the error for the first mass. Performance and robustness of the algorithms are compared when model errors are introduced in the system, showing that the optimisation-based approach can handle larger model uncertainties. It is illustrated that the performance of the overall system, when considering position of the second mass, is the practical limit compared to the limiting factor of the robustness of the ILC algorithms.

  • 176.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Experimental Evaluation of ILC Applied to a Six Degrees-of-Freedom Industrial Robot2007In: Proceedings of the 2007 European Control Conference, 2007Conference paper (Refereed)
    Abstract [en]

    Experimental evaluation of an Iterative Learning Control (ILC) algorithm is presented. The ILC algorithm is applied to all motors of a large size commercial six degrees-of-freedom industrial robot in order to minimise the error measured on the motor angles. The performance of the algorithm is evaluated with respect to the operating point of the robot, the programmed tool velocity, and the design variables of the ILC algorithm. The chosen movements are intended to represent typical paths in a laser cutting application. Even though a fairly simple ILC algorithm is applied, the error reduction is substantial after only five iterations and the algorithm shows good robustness properties.

  • 177.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Experimental Evaluation of ILC Applied to a Six Degrees-of-Freedom Industrial Robot2006Report (Other academic)
    Abstract [en]

    Experimental evaluation of an Iterative Learning Control (ILC) algorithm is presented. The ILC algorithm is applied to all motors of a large size commercial six degrees-of-freedom industrial robot in order to minimise the error measured on the motor angles. The performance of the algorithm is evaluated with respect to the operating point of the robot, the programmed tool velocity, and the design variables of the ILC algorithm. The chosen movements are intended to represent typical paths in a laser cutting application. Even though a fairly simple ILC algorithm is applied, the error reduction is substantial after only five iterations and the algorithm shows good robustness properties.

  • 178.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Performance and Robustness of ILC Applied to Flexible Systems2008In: Proceedings of Reglermöte 2008, 2008, p. 210-216Conference paper (Other academic)
    Abstract [en]

    When an ILC algorithm is applied to an industrial robot, the goal is to move the tool along a desired trajectory, while only the motor position can be measured. In this paper aspects of robustness and performance are discussed when an ILC algorithm is applied to a flexible two-mass system. It is shown that the stabilising controller of the two-mass system also directly affects the robustness properties of the ILC algorithm. A classical non-causal P-ILC algorithm and a model-based ILC design using optimisation are applied to the system, based on the error for the first mass. Performance and robustness of the algorithms are compared when model errors are introduced in the system, showing that the optimisation-based approach can handle larger model uncertainties. It is illustrated that the performance of the overall system, when considering position of the second mass, is the practical limit compared to the limiting factor of the robustness of the ILC algorithms.

  • 179.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Performance of ILC Applied to a Flexible Mechanical System2009In: Proceedings of European Control Conference (ECC), 2009, p. 1511-1516Conference paper (Refereed)
    Abstract [en]

    ILC is traditionally applied to systems where the controlled variable is the measured variable. However, in standard industrial robots only the motor angles are measured, while the control objective is to follow a tool path. A modern industrial robot is flexible, and assuming that the mechanical flexibilities are concentrated to the robot joints (elastic gearboxes), a flexible two-mass model can be used to describe a single joint. A P-ILC algorithm is applied to the two-mass model, based on only measured angle of the first mass (motor angle) or estimated angle for the second mass (tool angle). Robustness of the algorithm, and performance when model errors are introduced in the model, are discussed considering the error of the tool angle. First, it can be concluded for a flexible system that the characteristics of the motor-angle reference is essential for the resulting tool angle when the tool angle cannot be measured. Second, using an estimate of the tool angle instead of the explicit motor angle in the ILC update reduces the tool-angle error significantly.

  • 180.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Performance of ILC Applied to a Flexible Mechanical System2008Report (Other academic)
    Abstract [en]

    ILC is traditionally applied to systems where the controlled variable is the measured variable. However, in standard industrial robots only the motor angles are measured, while the control objective is to follow a tool path. A modern industrial robot is flexible, and assuming that the mechanical flexibilities are concentrated to the robot joints (elastic gearboxes), a flexible two-mass model can be used to describe a single joint. A P-ILC algorithm is applied to the two-mass model, based on only measured angle of the first mass (motor angle) or estimated angle for the second mass (tool angle). Robustness of the algorithm, and performance when model errors are introduced in the model, are discussed considering the error of the tool angle. First, it can be concluded for a flexible system that the characteristics of the motor-angle reference is essential for the resulting tool angle when the tool angle cannot be measured. Second, using an estimate of the tool angle instead of the explicit motor angle in the ILC update reduces the tool-angle error significantly.

  • 181.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Analysis of Methods for Multivariable Frequency Response Function Estimation in Closed Loop2007Report (Other academic)
    Abstract [en]

    Estimation methods for the multivariable frequency response function are analyzed, both in open and closed loop. Expressions for the bias and covariance are derived and the usefulness of these expressions is illustrated in simulations of an industrial robot where the different estimators are compared. The choice of estimator depends on the signal-to- noise ratio as well as the measurement setup and a bias-variance trade-off.

  • 182.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Analysis of Methods for Multivariable Frequency Response Function Estimation in Closed Loop2007In: Proceedings of the 46th IEEE Conference on Decision and Control, 2007, p. 4881-4888Conference paper (Refereed)
    Abstract [en]

    Estimation methods for the multivariable frequency response function are analyzed, both in open and closed loop. Expressions for the bias and covariance are derived and the usefulness of these expressions is illustrated in simulations of an industrial robot where the different estimators are compared. The choice of estimator depends on the signal-to- noise ratio as well as the measurement setup and a bias-variance trade-off.

  • 183.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Detection and Estimation of Nonlinear Distortions in Industrial Robots2006In: Proceedings of the 23rd IEEE Instumentation and Measurement Technology Conference, 2006, p. 1913-1918Conference paper (Refereed)
    Abstract [en]

    System identification in robotics often involves the estimation of linear models characterizing the behavior in certain operating points. In this paper, a method for the detection and estimation of nonlinear distortions in an estimated frequency response function (FRF) has successfully been applied to experimental data from an industrial robot. The results show that nonlinear distortions areindeed present and cause larger variability in the FRF than the measurement noise contributions.

  • 184.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Detection and Estimation of Nonlinear Distortions in Industrial Robots2006Report (Other academic)
    Abstract [en]

    System identification in robotics often involves the estimation of linear models characterizing the behavior in certain operating points. In this paper, a method for the detection and estimation of nonlinear distortions in an estimated frequency response function (FRF) has successfully been applied to experimental data from an industrial robot. The results show that nonlinear distortions areindeed present and cause larger variability in the FRF than the measurement noise contributions.

  • 185.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of Nonlinear Effects in Frequency Domain Identification of Industrial Robots2008In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 57, no 4, p. 856-863Article in journal (Refereed)
    Abstract [en]

    A method for the detection and estimation of nonlinear distortions when identifying multivariable frequency response functions (FRF) is considered. The method is successfully applied to experimental data from an industrial robot, collected in closed loop. The results show that nonlinear distortions are indeed present and cause larger variability in the FRF than the measurement noise contributions.

  • 186.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation of nonlinear effects in frequency-domain identification of industrial robots2008In: IEEE Transactions on Instrumentation and Measurement, Braunschweig, Germany, 2008, p. 856-863Conference paper (Other academic)
    Abstract [en]

    A method for the detection and estimation of nonlinear distortions when identifying multivariable frequency response functions (FRF) is considered. The method is successfully applied to experimental data, which were collected in closed loop, from an industrial robot. The results show that nonlinear distortions are indeed present and cause larger variability in the FRF than the measurement-noise contributions.

  • 187.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nonlinear Gray-Box Identification of a Flexible Manipulator2007In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939Article in journal (Other academic)
    Abstract [en]

    A three-step procedure for time-domain nonlinear gray-box identification of an industrial manipulator containing flexibilities is studied. The aim of the first two steps is to obtain good initial values for the third prediction error minimization step. In the first step, rigid body dynamics and friction are identified using a separable least-squares method. In the second step, initial values for flexibilities are obtained using an inverse eigenvalue method. Finally, in the last step, the remaining parameters of a nonlinear graybox model are identified directly in the time domain using prediction error minimization.

  • 188.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nonlinear Grey-Box Identification of Industrial Robots Containing Flexibilities2005In: Proceedings of the 16th IFAC World Congress, 2005, p. 59-59Conference paper (Refereed)
    Abstract [en]

    Nonlinear grey-box identification of industrial robots is considered. A three-step identification procedure is proposed in which parameters for rigid body dynamics, friction and flexibilites can be identified only using measurements on the motor. In the first two steps, good initial parameter estimates are derived which are used in the last step, where the parameters of a nonlinear physically parameterized model are identified directly in the time domain. The procedure is examplifed using real data from an experimental industrial robot.

  • 189.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nonlinear Grey-Box Identification of Industrial Robots Containing Flexibilities2004Report (Other academic)
    Abstract [en]

    Nonlinear grey-box identification of industrial robots is considered. A three-step identification procedure is proposed in which parameters for rigid body dynamics, friction and flexibilites can be identified only using measurements on the motor. In the first two steps, good initial parameter estimates are derived which are used in the last step, where the parameters of a nonlinear physically parameterized model are identified directly in the time domain. The procedure is examplifed using real data from an experimental industrial robot.

  • 190.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, University Library.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nonlinear Identification of a Physically Parameterized Robot Model2006In: Proceedings of the 14th IFAC Symposium on System Identification, 2006, p. 143-148Conference paper (Refereed)
    Abstract [en]

    In the work presented here, a three-step identification procedure for rigid body dynamics, friction, and flexibilities, introduced in (Wernholt and Gunnarsson, 2005), will be utilized and extended. Using the procedure, the parameters can be identified only using motor measurements. In the first step, rigid body dynamics and friction will be identified using a separable least squares method, where a friction model describing the Striebeck effect is used. In the second step, initial values for flexibilities are obtained using inverse eigenvalue theory. Finally, in the last step, the remaining parameters of a nonlinear physically parameterized model are identified directly in the time domain. The procedure is exemplified using real data from an experimental industrial robot.

  • 191.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nonlinear Identification of a Physically Parameterized Robot Model2006Report (Other academic)
    Abstract [en]

    In the work presented here, a three-step identification procedure for rigid body dynamics, friction, and flexibilities, introduced in (Wernholt and Gunnarsson, 2005), will be utilized and extended. Using the procedure, the parameters can be identified only using motor measurements. In the first step, rigid body dynamics and friction will be identified using a separable least squares method, where a friction model describing the Striebeck effect is used. In the second step, initial values for flexibilities are obtained using inverse eigenvalue theory. Finally, in the last step, the remaining parameters of a nonlinear physically parameterized model are identified directly in the time domain. The procedure is exemplified using real data from an experimental industrial robot.

  • 192.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On the Use of a Multivariable Frequency Response Estimation Method for Closed Loop Identification2004Report (Other academic)
    Abstract [en]

    A method for estimating the Multivariable Frequency Response Function using closed loop data is studied. An approximate expression for the estimation error is derived, and using this expression some properties of the estimation error can be explained. Of particular interest is how the model quality is affected by the properties of the disturbances, the choice of excitation signal in the different input channels, the feedback and the properties of the system itself. The expression is illustrated by simulation data from an industrial robot.

  • 193.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On the Use of a Multivariable Frequency Response Function Estimation Method for Closed Loop Identification2004In: Proceedings of the 43rd IEEE Conference on Decision and Control, 2004, p. 827-832Conference paper (Refereed)
    Abstract [en]

    A method for estimating the Multivariable Frequency Response Function using closed loop data is studied. An approximate expression for the estimation error is derived, and using this expression some properties of the estimation error can be explained. Of particular interest is how the model quality is affected by the properties of the disturbances, the choice of excitation signal in the different input channels, the feedback and the properties of the system itself. The expression is illustrated by simulation data from an industrial robot.

  • 194.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hanssen, Sven
    ABB Automation Technologies, Sweden.
    Moberg, Stig
    ABB Automation Technologies, Sweden.
    On the Use of a Multivariable Frequency Response Identification Method in the Presence of Periodic Disturbances2003Report (Other academic)
    Abstract [en]

    A method for estimating the Multivariable Frequency Response Function (MFRF) is evaluated with respect to different disturbance properties and excitation signals. For the robot application, disturbances are mainly of a periodic nature, and Gaussian disturbance descriptions, which are often used in identification literature, do not give the same result. It is shown that the averaging technique over multiple periods does not work as well for periodic disturbances as for Gaussian disturbances. The chirp excitation signal might be a better choice than multisine to reduce the influence of periodic disturbances. The main reason for this is a varying operating point.

  • 195.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Recursive Identification of Physical Parameters in a Flexible Robot Arm2002Report (Other academic)
    Abstract [en]

    Recursive identification of physically parameterized models of continuous time systems is considered. As an example a model of a single link flexible robot arm is considered. The aim of the identification is to generate on-line estimates of physical parameters that can be used for, e.g., diagnosis purposes. For evaluation the algorithm is applied to data from an industrial robot, and three important parameters are identified using only measurements of the motor angle.

  • 196.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed-Loop Identification of an Industrial Robot Containing Flexibilities2001Report (Other academic)
    Abstract [en]

    Closed-loop identification of an industrial robot of the type ABB IRB 1400 is considered. Data are collected when the robot is subject to feedback control and moving around axis one. Both black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities. It is found that a model consisting of three-masses connected by springs and dampers gives a good description of the dynamics of the robot.

  • 197.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed-Loop Identification of an Industrial Robot Containing Flexibilities2003In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 11, no 3, p. 291-300Article in journal (Refereed)
    Abstract [en]

    Closed-loop identification of an industrial robot of the type ABB IRB 1400 is considered. Data are collected when the robot is subject to feedback control and moving around axis one. Both black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities. It is found that a model consisting of three-masses connected by springs and dampers gives a good description of the dynamics of the robot.

1234 151 - 197 of 197
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