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  • 1.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    LQG Control of a Flexible Servo1999In: Proceedings of the Second Conference on Computer Science and Systems Engineering, 1999, p. 125-132Conference paper (Other academic)
    Abstract [en]

    LQG control of a flexible servo system is considered using a linear two-mass model. The control system is mainly based on the measured position before the flexibility, but the use of acceleration feedback is also studied. Some aspects of regulator stability are considered.

  • 2.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    LQG Control of a Flexible Servo1999Report (Other academic)
    Abstract [en]

    LQG control of a flexible servo system is considered using a linear two-mass model. The control system is mainly based on the measured position before the flexibility, but the use of acceleration feedback is also studied. Some aspects of regulator stability are considered and some a-PID- based sontrol system are also examined.

  • 3.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Regulator Stability in Control of Flexible Mechanical Systems2001In: Proceedings of the 32nd International Symposium on Robotics, 2001Conference paper (Refereed)
    Abstract [en]

    Feed-back control of a flexible mechanical system is considered using a linear two-mass model. It is found that unstable controllers often occur when the performance requirements of the closed loop system are made too high. It is illustrated how potential windup problems caused by unstable controllers in combination with input saturations can be handled. A remaining consequence of the use of unstable controllers is that it puts stronger requirements on the accuracy of the model. This is illustrated using the Bode integral.

  • 4.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Regulator Stability in Control of Flexible Mechanical Systems2001Report (Other academic)
    Abstract [en]

    Feed-back control of a flexible mechanical system is considered using a linear two-mass model. It is found that unstable controllers often occur when the performance requirements of the closed loop system are made too high. It is illustrated how potential windup problems caused by unstable controllers in combination with input saturations can be handled. A remaining consequence of the use of unstable controllers is that it puts stronger requirements on the accuracy of the model. This is illustrated using the Bode integral.

  • 5.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Recursive Identification of Physical Parameters in a Flexible Robot Arm2002In: Proceedings of the 4th Asian Control Conference, 2002Conference paper (Refereed)
    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.

  • 6.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Recursive Identification of Physical Parameters in a Flexible Robot Arm2002In: Proceedings of Reglermöte 2002, 2002Conference paper (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 online 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.

  • 7.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Recursive Identification of Physical Parameters in a Flexible Robot Arm2004In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 6, p. 407-414Article in journal (Refereed)
    Abstract [en]

    Recursive identification of a physically parameterized model of a single link flexible robot arm is considered. The parameters are estimated using a recursive prediction error method applied to a linear continuous time model structure and discrete time data. The algorithm is applied to real data from an industrial robot, and three important parameters are identified using only measurements of the motor angle. The experiments show that the particular parameter that is estimated will have big influence on the algorithm behavior.

  • 8.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Tjärnström, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Aberger, Martin
    Johannes Kepler University Linz, Austria.
    Modeling and Identification of a Mechanical Industrial Manipulator2002In: Proceedings of Reglermöte 2002, 2002, p. 250-255Conference paper (Other academic)
    Abstract [en]

    This paper covers modeling and identification of one joint of an industrial robot manipulator including flexibilities. It is shown how models can be built in the Modelica graphical environment and how these models can be transformed into a mathematical state space description which directly can be used for identification. A motivation to use linear models for modeling of the robot arm is given. This includes an analysis of the nonlinearities in the input/output data from the actual robot using a special kind of input signal. Identification and validation of the physically parameterized models are also covered.

  • 9.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Tjärnström, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Aberger, Martin
    Johannes Kepler University Linz, Austria.
    Modeling and Identification of a Mechanical Industrial Manipulator2002In: Proceedings of the 15th IFAC World Congress, 2002, p. 852-852Conference paper (Refereed)
    Abstract [en]

    This paper covers modeling and identification of one joint of an industrial robot manipulator including flexibilities. It is shown how models can be built in the Modelica graphical environment and how these models can be transformed into a mathematical state space description which directly can be used for identification. A motivation to use linear models for modeling of the robot arm is given. This includes an analysis of the nonlinearities in the input/output data from the actual robot using a special kind of input signal. Identification and validation of the physically parameterized models are also covered.

  • 10.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Tjärnström, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Aberger, Martin
    Johannes Kepler University Linz, Austria.
    Modeling and Identification of a Mechanical Industrial Manipulator2002Report (Other academic)
    Abstract [en]

    This paper covers modeling and identification of one joint of an industrial robot manipulator including flexibilities. It is shown how models can be built in the Modelica graphical environment and how these models can be transformed into a mathematical state space description which directly can be used for identification. A motivation to use linear models for modeling of the robot arm is given. This includes an analysis of the nonlinearities in the input/output data from the actual robot using a special kind of input signal. Identification and validation of the physically parameterized models are also covered.

  • 11.
    Wernholt, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Modeling and Control of a Bending Backwards Industrial Robot2003Report (Other academic)
    Abstract [en]

    In this work we have looked at various parts of modeling of robots. First the rigid body motion is studied, spanning from kinematics to dynamics and path and trajectory generation. We have also looked into how to extend the rigid body model with flexible gear-boxes and how this could be incorporated with Robotics Toolbox. A very simple feedforward control based on the rigid model is applied in addition to PID control and in the simulations the overshoot is halved compared to only PID control. We have also tried LQ control and in our simulations the effect of torque disturbances on the arm has been lowered by a factor five, compared to diagonal PID controllers.

  • 12.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed Loop Identification of the Physical Parameters of an Industrial Robot2001In: Proceedings of the Third Conference on Computer Science and Systems Engineering, 2001, p. 191-198Conference paper (Other academic)
    Abstract [en]

    This paper discusses experimental identication of a flexible robot under strong feedback. Black-box models are compared with physically parameterized models. The parameters in the physical models and the blackbox models are identified from the input-output data using prediction error methods. We also investigate the importance of noise models when performing identication under strong feedback. The robot that we use is a commercial ABB robot, IRB 1400.

  • 13.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed Loop Identification of the Physical Parameters of an Industrial Robot2001In: Proceedings of the 32nd International Symposium on Robotics, 2001Conference paper (Refereed)
    Abstract [en]

    This paper discusses experimental identication of a flexible robot under strong feedback. Black-box models are compared with physically parameterized models. The parameters in the physical models and the blackbox models are identified from the input-output data using prediction error methods. We also investigate the importance of noise models when performing identification under strong feedback. The robot that we use is a commercial ABB robot, IRB 1400.

  • 14.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed Loop Identification of the Physical Parameters of an Industrial Robot2000Report (Other academic)
    Abstract [en]

    This paper discusses experimental identication of a flexible robot under strong feedback. Black-box models are compared with physically parameterized models. The parameters in the physical models and the blackbox models are identified from the input-output data using prediction error methods. We also investigate the importance of noise models when performing identication under strong feedback. The robot that we use is a commercial ABB robot, IRB 1400.

  • 15.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Modeling, Fault Detection and Fault Isolation of Valve and Pipe System2000Report (Other academic)
    Abstract [en]

    Valve and pipe systems are used in many areas. Often there is redundancy in the system. If one valve breaks it may be possible to lead the gas (or fluid) another way. To do this automatically we have to be able to detect and isolate faults. In this report, we show a way to use discrete event dynamical system models for analyzing where to put sensors in a valve and pipe system.

  • 16.
    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.

  • 17.
    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.

  • 18.
    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.

  • 19.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Tjärnström, Fredrik
    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.
    Modeling of Industrial Robot for Identification, Monitoring and Control2002In: Proceedings of the 2002 International Symposium on Advanced Control of Industrial Processes, 2002Conference paper (Refereed)
    Abstract [en]

    In this paper we study the problem of a modeling, identifying, and monitoring an industrial robot. We start by showing how a robot can be modeled in increasing degree of accuracy using high end tools such as MathModelica. This model can be transformed semi-automatically into a minimal state-space form which in turn can be used for identification. Moreover, the physically connected equations can be identified recursively, making it possible to monitor critical parts of the robot. When attached to a well trimmed detection scheme this provides a big help for operators, who easily can track problems with the process.

  • 20.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Tjärnström, Fredrik
    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.
    Modeling of Industrial Robot for Identification, Monitoring and Control2002Report (Other academic)
    Abstract [en]

    In this paper we study the problem of a modeling, identifying, and monitoring an industrial robot. We start by showing how a robot can be modeled in increasing degree of accuracy using high end tools such as MathModelica. This model can be transformed semi-automatically into a minimal state-space form which in turn can be used for identification. Moreover, the physically connected equations can be identified recursively, making it possible to monitor critical parts of the robot. When attached to a well trimmed detection scheme this provides a big help for operators, who easily can track problems with the process.

1 - 20 of 20
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