| 1. |
- Markusson, Ola, 1971-, et al.
(författare)
-
Iterative Learning Control of Nonlinear Non-Minimum Phase Systems and its Application to System and Model Inversion
- 2002
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this contribution we place ILC in the realm of numerical optimization. This clarifies the role played by the design variables and how they affect e.g. convergence properties. We give a model based interpretation of these design variables and also a sufficient condition for convergence of ILC which is similar in spirit to the sufficient and necessary condition previously derived for linear systems. This condition shows that the desired performance has to be traded against modelling accuracy. Finally, one of the main benefits of ILC when non-minimum phase systems are concerned, the possibility of non-causal control, is given a comprehensive coverage.
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| 2. |
- Andersson, Magnus, et al.
(författare)
-
A Simulation and Animation Tool for Studying Multivariable Control
- 2002
-
Ingår i: Proceedings of the 15th IFAC World Congress. - 9783902661746 ; , s. 1432-1432
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Konferensbidrag (refereegranskat)abstract
- A simulation and animation tool for education in multivariable control is presented. The purpose of the tool is to support studies of various aspects of multivariable dynamical systems and design of multivariable feedback control systems. Different ways to use this kind of tool in control education are also presented and discussed.
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| 3. |
- Ardeshiri, Tohid, 1980-, et al.
(författare)
-
Convex Optimization Approach for Time-Optimal Path Tracking of Robots with Speed Dependent Constraints
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The task of generating time optimal trajectories for a six degrees of freedom industrial robot is discussed and an existing convex optimization formulation of the problem is extended to include new types of constraints. The new constraints are speed dependent and can be motivated from physical modeling of the motors and the drive system. It is shown how the speed dependent constraints should be added in order to keep the convexity of the overall problem. A method to, conservatively, approximate the linear speed dependent constraints by a convex constraint is also proposed. A numerical example proves versatility of the extension proposed in this paper.
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| 4. |
- Ardeshiri, Tohid, 1980-, et al.
(författare)
-
Convex Optimization Approach for Time-Optimal Path Tracking of Robots with Speed Dependent Constraints
- 2011
-
Ingår i: Proceedings of the 18th IFAC World Congress. - : IFAC. - 9783902661937 ; , s. 14648-14653
-
Konferensbidrag (refereegranskat)abstract
- The task of generating time optimal trajectories for a six degrees of freedom industrial robot is discussed and an existing convex optimization formulation of the problem is extended to include new types of constraints. The new constraints are speed dependent and can be motivated from physical modeling of the motors and the drive system. It is shown how the speed dependent constraints should be added in order to keep the convexity of the overall problem. A method to, conservatively, approximate the linear speed dependent constraints by a convex constraint is also proposed. A numerical example proves versatility of the extension proposed in this paper.
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| 5. |
- Axelsson, Patrik, 1985-, et al.
(författare)
-
Bayesian Methods for Estimating Tool Position of an Industrial Manipulator
- 2012
-
Ingår i: Proceedings of Reglermöte 2012.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- State estimation of a flexible industrial manipulator is presented using experimental data. The problem is formulated in a Bayesian framework where the extended Kalman filter and particle filter are used. The filters use the joint positions on the motor side of the gearboxes as well as the acceleration at the end-effector as measurements and estimates the corresponding joint angles on the arm side of the gearboxes. The techniques are verified on a state of the art industrial robot, and it is shown that the use of the acceleration at the end-effector improves the estimates significantly.
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| 6. |
- Axelsson, Patrik, 1985-, et al.
(författare)
-
Bayesian State Estimation of a Flexible Industrial Robot
- 2012
-
Ingår i: Control Engineering Practice. - : Elsevier. - 0967-0661 .- 1873-6939. ; 20:11, s. 1220-1228
-
Tidskriftsartikel (refereegranskat)abstract
- A sensor fusion method for state estimation of a flexible industrial robot is developed. By measuring the acceleration at the end-effector, the accuracy of the arm angular position, as well as the estimated position of the end-effector are improved. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; the extended Kalman filter and the particle filter. In a simulation study on a realistic flexible industrial robot, the angular position performance is shown to be close to the fundamental Cramér-Rao lower bound. The technique is also verified in experiments on an ABB robot, where the dynamic performance of the position for the end-effector is significantly improved.
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| 7. |
- Axelsson, Patrik, 1985-, et al.
(författare)
-
Extended Kalman Filter Applied to Industrial Manipulators
- 2010
-
Ingår i: Proceedings of Reglermöte 2010.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper summarizes previous work on tool position estimation on industrial manipulators, and emphasize the problems that must be taken care of in order to get a satisfied result. The acceleration of the robot tool, measured by an accelerometer, together with measurements of motor angles are used. The states are estimated with an extended Kalman filter. A method for tuning the covariance matrices for the noise, used in the observer, is suggested. The work has been focused on a robot with two degrees of freedom.
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| 8. |
- Axelsson, Patrik, 1985-, et al.
(författare)
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Method to Estimate the Position and Orientation of a Triaxial Accelerometer Mounted to an Industrial Manipulator
- 2012
-
Ingår i: Proceedings of the 10th IFAC Symposium on Robot Control. - 9783902823113 ; , s. 283-288
-
Konferensbidrag (refereegranskat)abstract
- A novel method to find the orientation and position of a triaxial accelerometer mounted on a six degrees-of-freedom industrial robot is proposed and evaluated on experimental data. The method consists of two consecutive steps, where the first is to estimate the orientation of the accelerometer from static experiments. In the second step the accelerometer position relative to the robot base is identified using accelerometer readings when the accelerometer moves in a circular path and where the accelerometer orientation is kept constant in a path fixed coordinate system. Once the accelerometer position and orientation are identified it is possible to use the accelerometer in robot model parameter identification and in advanced control solutions. Compared to previous methods, the accelerometer position estimation is completely new, whereas the orientation is found using an analytical solution to the optimisation problem. Previous methods use a parameterisation where the optimisation uses an iterative solver.
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| 9. |
- Axelsson, Patrik, 1985-, et al.
(författare)
-
Tool Position Estimation of a Flexible Industrial Robot using Recursive Bayesian Methods
- 2012
-
Ingår i: Proceedings of the 2012 IEEE International Conference on Robotics and Automation. - 9781467314039 - 9781467314046 ; , s. 5234-5239
-
Konferensbidrag (refereegranskat)abstract
- A sensor fusion method for state estimation of a flexible industrial robot is presented. By measuring the acceleration at the end-effector, the accuracy of the arm angular position is improved significantly when these measurements are fused with motor angle observation. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; one using the extended Kalman filter (EKF) and one using the particle filter (PF). The technique is verified on experiments on the ABB IRB4600 robot, where the accelerometer method is showing a significant better dynamic performance, even when model errors are present.
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| 10. |
- Björkman, Mattias, et al.
(författare)
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A New Concept for Motion Control of Industrial Robots
- 2008
-
Ingår i: Proceedings of the 17th IFAC World Congress. - Linköping : Linköping University Electronic Press. - 9783902661005
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Konferensbidrag (refereegranskat)abstract
- This paper gives a short summary of an industrial development work on model-based motion control. This development has resultet in high robot motion performance simultaneously with an efficient use of the installed drive system of the robot.
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| 11. |
- Enqvist, Martin, 1976-, et al.
(författare)
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The CDIO Initiative from an Automatic Control Project Course Perspective
- 2005
-
Ingår i: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 2283-2283
-
Konferensbidrag (refereegranskat)abstract
- The CDIO (Conceive Design Implement Operate) Initiative is explained, and some of the results at the Applied Physics and Electrical Engineering program at Linköping University, Sweden, are presented. A project course in Automatic Control is used as an example. The projects within the course are carried out using the LIPS (Linköping interactive project steering) model. An example of a project, the golf playing industrial robot, and the results from this project are also covered.
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| 12. |
- Enqvist, Martin, 1976-, et al.
(författare)
-
The CDIO Initiative from an Automatic Control Project Course Perspective
- 2004
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The CDIO (Conceive Design Implement Operate) Initiative is explained, and some of the results at the Applied Physics and Electrical Engineering program at Linköping University, Sweden, are presented. A project course in Automatic Control is used as an example. The projects within the course are carried out using the LIPS (Linköping interactive project steering) model. An example of a project, the golf playing industrial robot, and the results from this project are also covered.
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| 13. |
- Eriksson, Lars, 1970-, et al.
(författare)
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Improved Drive Cycle Following with an ILC Supported Driver Model
- 2015
-
Ingår i: 4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling ECOSM’15. - : The International Federation of Automatic Control (IFAC). ; , s. 347-353
-
Konferensbidrag (refereegranskat)abstract
- Drive cycle following is important for concept comparisons when evaluating vehicle concepts, but it can be time consuming to develop good driver models that can achieve accurate following of a specific velocity profile. Here, a new approach is proposed where a simple driver model based on a PID controller is extended with an Iterative Learning Control (ILC) algorithm. Simulation results using a nonlinear vehicle and control system model show that it is possible to achieve very good cycle following in a few iterations with little tuning effort. It is also possible to utilize the repetitive behavior in the drive cycle to accelerate the convergence of the ILC algorithm even further.
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| 14. |
- Fujimori, Atsushi, et al.
(författare)
-
A Gain Scheduling Control of Nonlinear Systems along a Reference Trajectory
- 2005
-
Ingår i: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 609-609
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.
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| 15. |
- Fujimori, Atsushi, et al.
(författare)
-
A Gain Scheduling Control of Nonlinear Systems along a Reference Trajectory
- 2004
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.
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| 16. |
- Gunnarsson, Svante, et al.
(författare)
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A Model Based Iterative Learning Control Method Applied to an Industrial Robot
- 1999
-
Ingår i: Proceedings of the Second Conference on Computer Science and Systems Engineering. - Linköping : Linköping University Electronic Press.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- A synthesis algorithm for the filters in a first order ILC is presented and applied on an industrial robot. The proposed ILC synthesis method is evaluated using two experiments on the robot. The first is a one-axis experiment where the system can be seen as a single servo. A modeling experiment is done to give input to the synthesis algorithm and then ILC is applied to the single axis showing a dramatic improvement in trajectory following. In the second experiment ILC is applied to a more complex multi axes motion where the robot draws a circle in a plane. The evaluation of the result is done using a pen mounted on the robot and it is evident that also on the arm-side an improved motion can be achieved. In both experiments the error converges to a stable level in about 5 iterations. Since a model is desired for the synthesis, an extra iteration has to be done for the modeling experiment. In this particular case a good path following can therefore be achieved after 6 iterations.
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| 17. |
- Gunnarsson, Svante, et al.
(författare)
-
A Short Introduction to Iterative Learning Control
- 1997
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- An introduction to Iterative Learning Control (ILC) is given. The basic principle behind ILC in both open loop and closed loop problems is explained. A general class of algorithms for updating of the ILC input signal is presented and the choice of the filters in the update algortihm is discussed with respect to convergence, robustness and disturbance sensitivity.
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| 18. |
- Gunnarsson, Svante, et al.
(författare)
-
Iterative Learning Control of a Flexible Mechanical System Using Accelerometers
- 2000
-
Ingår i: Proceedings of the 6th IFAC Symposium on Robot Control. - Linköping : Linköping University Electronic Press. - 0080435610 ; , s. 327-332
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Control of a flexible mechanical system using Iterative Learning Control (ILC) is studied using a linear two-mass model. The available signals are position of the first mass and acceleration of the second mass. An ILC algorithm using an estimate of the position of the second mass is evaluated in simulations showing promising properties.
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| 19. |
- Gunnarsson, Svante, et al.
(författare)
-
Iterative Learning Control of a Flexible Robot Arm Using Accelerometers
- 2003
-
Ingår i: Proceedings of Mekatronikmöte 2003. - Linköping : Linköping University Electronic Press.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Iterative learning control (ILC) is applied to a laboratory scale robot arm with joint flexibility. The ILC algorithm is based on an estimate of the arm angle, where the estimate is formed using measurements of the motor angle and the arm angular acceleration. The design of the ILC algorithm is based on a model obtained from system identification. The ILC algorithm is evaluated experimentally on the robot arm with good results.
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| 20. |
- Gunnarsson, Svante, et al.
(författare)
-
Iterative Learning Control of a Flexible Robot Arm Using Accelerometers
- 2004
-
Ingår i: Proceedings of the 2004 IEEE Conference on Control Applications. - 0780386337 ; , s. 1012-1016 vol.2
-
Konferensbidrag (refereegranskat)abstract
- Iterative learning control (ILC) is applied to a laboratory scale robot arm with joint exibility. The ILC algorithm is based on an estimate of the arm angle, where the estimate is formed using measurements of the motor angle and the arm angular acceleration. The design of the ILC algorithm is based on a model obtained from system identication. The ILC algorithm is evaluated experimentally on the robot arm with good results.
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| 21. |
- Gunnarsson, Svante, et al.
(författare)
-
On the Design of ILC Algorithms using Optimization
- 2000
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Design of Iterative Learning Control (ILC) algorithms using optimization is considered. By forming a quadratic criterion in the control error and the input signal using a nominal model of the system an ILC algorithm is derived. Special attention is paid to the frequency domain properties of the algorithm and to how it is able to handle non-minimum phase systems. A numerical example and an experiment carried out on an real industrial robot are presented.
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| 22. |
- Gunnarsson, Svante, et al.
(författare)
-
On the Design of ILC Algorithms using Optimization
- 2001
-
Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 37:12, s. 2011-2016
-
Tidskriftsartikel (refereegranskat)abstract
- Iterative learning control (ILC) based on minimization of a quadratic criterion in the control error and the input signal is considered. The focus is on the frequency domain properties of the algorithm, and how it is able to handle non-minimum phase systems. Experiments carried out on a commercial industrial robot are also presented.
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| 23. |
- Gunnarsson, Svante, et al.
(författare)
-
On the Disturbance Properties of High Order Iterative Learning Control Algorithms
- 2006
-
Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 42:11, s. 2031-2034
-
Tidskriftsartikel (refereegranskat)abstract
- The disturbance properties of high order iterative learning control (ILC) algorithms are considered. An error equation is formulated, and using statistical models of the load and measurement disturbances an equation for the covariance matrix of the control error vector is derived. The results are exemplified by analytic derivation of the covariance matrix for a second order ILC algorithm.
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| 24. |
- Gunnarsson, Svante, et al.
(författare)
-
On the Use of Accelerometers in Iterative Learning Control of a Flexible Robot Arm
- 2007
-
Ingår i: International Journal of Control. - : Taylor & Francis. - 0020-7179 .- 1366-5820. ; 80:3, s. 363-373
-
Tidskriftsartikel (refereegranskat)abstract
- Iterative learning control (ILC) is applied to a robot arm with joint flexibility. The ILC algorithm uses an estimate of the arm angle, where the estimate is computed using measurements of the motor angle and the arm angular acceleration. The design of the ILC algorithm is evaluated experimentally on a laboratory scale robot arm with good results.
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| 25. |
- Gunnarsson, Svante, 1959-, et al.
(författare)
-
On the Use of Learning Control for Improved Performance in Robot Control Systems
- 1997
-
Ingår i: Proceedings of the 1997 European Control Conference. - Linköping : Linköping University Electronic Press.
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Iterative learning control applied to a simplified model of a robot arm is studied. The iterative learning control input signal is used in combination with conventional feed-back and feed-forward control, and the aim is to let the learning control signal handle the effects of unmodeled dynamics and friction. Convergence and robustness aspects of the choice of filters in the updating scheme of the iterative learning control signal are studied.
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| 26. |
- Gunnarsson, Svante, et al.
(författare)
-
Some Aspects of an Optimization Approach to Iterative Learning Control
- 1999
-
Ingår i: Proceedings of the 38th IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780352505 ; , s. 1581-1586 vol.2
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- An optimization approach to Iterative Learning Control (ILC) is considered. The ILC algorithm is formed by minimizing a quadratic criterion in the control error and input signal. A frequency domain interpretation of the derived updating algorithm is given. Experiments carried out on an ABB IRB 1400 are presented.
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| 27. |
- Gunnarsson, Svante, 1959-, et al.
(författare)
-
Some Experiences of the use of Iterative Learning Control for Performance Improvement in Robot Control Systems
- 1997
-
Ingår i: Proceedings of the 5th IFAC Symposium on Robot Control. - Linköping : Linköping University Electronic Press. - 0080430260 ; , s. 379-
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Some aspects of the use of learning control for improved performance in robot control systems are studied. The learning control signal is used in combination with conventional feed-back and feed-forward control. The effects of disturbances, unmodeled dynamics and friction are studied theoretically and in simulations of a simplified model of a robot arm. Convergence and robustness aspects of the choice of filters in the updating scheme of the learning control signal are studied.
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| 28. |
- Gunnarsson, Svante, et al.
(författare)
-
Some Fundamental Limitations in Causal and CITE ILC
- 2004
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Some fundamental limitations of causal and Current Iteration Tracking Error (CITE) discrete time Iterative Learning Control (ILC) algorithms are stud- ied using time and frequency domain convergence criteria. Of particular interest are conditions for monotone convergence, and these are evaluated using a discrete- time version of Bode's integral theorem. A relation between the frequency domain convergence conditions and the time-domain monotone convergence criterion is also discussed.
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| 29. |
- Haghshenas, Hamed, 1990-
(författare)
-
Time-Optimal Cooperative Path Tracking for Multi-Robot Systems
- 2021
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Robotic systems are nowadays the key technology in a wide variety of applications. The increasing demand for performance of robotic systems is often met by employing a team of cooperating robots for a specific task.When the task carried out by the robots involves manipulation of an object, the multi-robot system is said to perform a cooperative manipulation task.Cooperative manipulation is an important capability for extending the domain of robotic applications.This thesis studies the time-optimal path tracking problem for a cooperative manipulation scenario where an object is rigidly grasped by multiple manipulators. The goal is to move the object along a predefined geometric path in minimum time while satisfying the imposed constraints on the motion. First, it is shown that the time-optimal path tracking problem for cooperative manipulators can be cast as a convex optimization problem. A fundamental property of convex optimization problems is that any locally optimal solution is also a globally optimal one. Furthermore, by recognizing and formulating a problem as a convex optimization problem, it can be solved very reliably and efficiently using interior-point or other methods for convex optimization.These results are presented in two separate studies. In the first one which is a preliminary study, the manipulation setup is a particular setup comprised of two planar manipulators and a bar. Furthermore, the load distribution among the manipulators is considered to be equal. The second study extends the results in the preliminary study to a general scenario with $N$ generic manipulators and an object with a desired orientation during the motion. Here, the load distribution among the manipulators is determined via a generic pseudo-inverse of the grasp matrix that can be chosen by the user.The freedom in the choice of the pseudo-inverse allows to consider different load distributions which can be exploited to account for the potential differences in the capabilities of the manipulators.The second part of this thesis is devoted to finding load distributions that are free of internal forces. A drawback of using multiple manipulators in a cooperative manipulation task is that internal forces can be introduced.Internal forces are forces exerted by the end-effectors at the grasping points that do not contribute to the motion of the manipulated object. While a certain amount of such forces can be useful in some cases, in general they must be avoided to prevent object damage and unnecessary effort of the manipulators.This thesis proposes a new approach to obtain internal force-free load distributions.The proposed approach results in a new pseudo-inverse of the grasp matrix parameterized by coefficients that have the meaning of the inertial parameters of some parts of the object. The freedom in the choice of the parameters of the pseudo-inverse allows to assign different loads to the manipulators. This can be exploited to account for the differences in the power capabilities of the manipulators.The results are further explored for scenarios where the object is three-dimensional and convex and has uniform mass density. Finally, the proposed pseudo-inverse is combined with the results in the first part of the thesis to solve the problem of time-optimal cooperative path tracking subject to zero internal forces during the motion.
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| 30. |
- Hedberg, Erik, et al.
(författare)
-
Comparing Feedback Linearization and Jacobian Linearization for LQ Control of an Industrial Manipulator
- 2018
-
Ingår i: Proccedings of the 12TH IFAC SYMPOSIUM ON ROBOT CONTROL.
-
Konferensbidrag (refereegranskat)abstract
- Feedback linearization is compared to Jacobian linearization for LQ control of atwo-link industrial manipulator. A method for obtaining equivalent nominal performance forboth control designs is introduced. An experimentally verified benchmark model with industrialrelevance is used for comparing the designs. Results do not show any conclusive advantages ofFeedback linearization.
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| 31. |
- Hedberg, Erik, 1986-
(författare)
-
Control, Models and Industrial Manipulators
- 2020
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The two topics at the heart of this thesis are how to improve control of industrial manipulators and how to reason about the role of models in automatic control.On industrial manipulators, two case studies are presented. The first investigates estimation with inertial sensors, and the second compares control by feedback linearization to control based on gain-scheduling.The contributions on the second topic illustrate the close connection between control and estimation in different ways. A conceptual model of control is introduced, which can be used to emphasize the role of models as well as the human aspect of control engineering. Some observations are made regarding block-diagram reformulations that illustrate the relation between models, control and inversion. Finally, a suggestion for how the internal model principle, internal model control, disturbance observers and Youla-Kucera parametrization can be introduced in a unified way is presented.
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| 32. |
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| 33. |
- Karlsson, Rickard, 1970-, et al.
(författare)
-
Bayesian Position Estimation of an Industrial Robot using Multiple Sensors
- 2004
-
Ingår i: Proceedings of the 2004 IEEE Conference on Control Applications. - Linköping : Linköping University Electronic Press.
-
Konferensbidrag (refereegranskat)abstract
- A modern industrial robot control system is often only based upon measurements from the motors of the manipulator. To perform good tra-ectory tracking on the arm side of the robot a very accurate description of the system must therefore be used. In the paper a sensor fusion technique is presented to achieve good estimates of the position of the robotusing a very simple model. By using information from an accelerometer at the tool of the robot the effect of unmodelled dynamics can be measured. The estimate of the tool position can be improved to enhance accuracy. We formulate the computation of the position as a Bayesian estimation problem and propose two solutions. The first solution uses the extended Kalman fillter (EKF) as a fast but linearized estimator. The second uses the particle fillter which can solve the Bayesian estimation problem without linearizations or any Gaussian noise assumptions. Since the aim is to use the positions estimates to improve position with an iterative learning control method, no computational constraints arise. The methods are applied to experimental data from an ABB IRB1400 commercial industrialrobot and to data from a simulation of a realistic flexible robot model, showing a significant improvement in position accuracy.
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| 34. |
- Karlsson, Rickard, 1970-, et al.
(författare)
-
Bayesian State Estimation of a Flexible Industrial Robot
- 2005
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A sensor fusion method for state estimation of a flexible industrial robot is developed. By measuring the acceleration at the end-effector, the accuracy of the arm angular position, as well as the estimated position of the end-effector are improved. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; the extended Kalman filter and the particle filter. In a simulation study on a realistic flexible industrial robot, the angular position performance is shown to be close to the fundamental Cramér-Rao lower bound. The technique is also verified in experiments on an ABB robot, where the dynamic performance of the position for the end-effector is significantly improved.
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| 35. |
- Karlsson, Rickard, 1970-, et al.
(författare)
-
Position Estimation and Modeling of a Flexible Industrial Robot
- 2005
-
Ingår i: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 1311-1311
-
Konferensbidrag (refereegranskat)abstract
- A sensor fusion technique is presented and it is shown to achieve good estimates of the position for a 3 degrees-of-freedom industrial robot model. By using an accelerometer the estimate of the tool position accuracy can be improved. The computation of the position is formulated as a Bayesian estimation problem and two solutions are proposed. One using the extended Kalman filter and one using the particle filter. Since the aim is to use the positions estimates to improve trajectory tracking with an iterative learning control method, no computational constraints arise. In an extensive simulation study the performance is compared to the Cramér-Rao lower bound. A significant improvement in position accuracy is achieved using the sensor fusion technique.
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| 36. |
- Karlsson, Rickard, 1970-, et al.
(författare)
-
Position Estimation and Modeling of a Flexible Industrial Robot
- 2004
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A sensor fusion technique is presented and it is shown to achieve good estimates of the position for a 3 degrees-of-freedom industrial robot model. By using an accelerometer the estimate of the tool position accuracy can be improved. The computation of the position is formulated as a Bayesian estimation problem and two solutions are proposed. One using the extended Kalman filter and one using the particle filter. Since the aim is to use the positions estimates to improve trajectory tracking with an iterative learning control method, no computational constraints arise. In an extensive simulation study the performance is compared to the Cramér-Rao lower bound. A significant improvement in position accuracy is achieved using the sensor fusion technique.
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| 37. |
- Karlsson, Rickard, 1970-, et al.
(författare)
-
Sensor Fusion for Position Estimation of an Industrial Robot
- 2004
-
Ingår i: Proceedings of Reglermöte 2004. - Linköping : Linköping University Electronic Press.
-
Konferensbidrag (refereegranskat)abstract
- A modern industrial robot control system is often based only upon measurements from the motors of the manipulator. Hence to follow a trajectory with the tool an accurate description of the system must be used. In the paper a sensor fusion technique is presented to achieve good estimates of the position of the robot using a simple model. By using information from an accelerometer the effect of unmodelled dynamics can be measured. Hence, the estimate of the tool position can be improved to enhance the positioning. We formulate the computation of the position as a Bayesian estimation problem and propose two solutions. First using the extended Kalman filter EKF as a fast but linearized estimator. Second the particle filter which can solve the Bayesian estimation problem without linearizations or any Gaussian noise assumptions. Since the aim is to use the estimates to improve position accuracy using an iterative learning control method, no computational constraints arises. The methods are applied to experimental data from an ABBIRB1400 commercial industrial robot. We also discuss some preliminary results from using a detailed simulation model.
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| 38. |
- Markusson, Ola, et al.
(författare)
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Iterative learning control of nonlinear non-minimum phase systems and its application to system and model inversion
- 2001
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Ingår i: PROCEEDINGS OF THE 40TH IEEE CONFERENCE ON DECISION AND CONTROL. - 0780370619 ; , s. 4481-4482
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Konferensbidrag (refereegranskat)abstract
- In this contribution we present a model based method for reference tracking in the Iterative Learning Control (ILC) framework. The method can be applied to nonlinear, possibly non-minimum phase, systems. The idea is to use the inverse of a linearized model in the ILC update. In the non-minimum phase case, the batch property of ILC is explored by means of non-causal filtering. Apart from reference tracking, this method is useful for system and model inversion - a problem that arises in many disciplines where nonlinear systems and models are involved, e.g. maximum likelihood identification and input design for identification for control. The method is illustrated on a numerical example.
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| 39. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
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A Frequency Domain Analysis of a Second Order Iterative Learning Control Algorithm
- 1999
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Ingår i: 38th IEEE Conference on Decision and Control,1999. - Pheonix, AZ, USA : IEEE. ; , s. 1587-
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Konferensbidrag (refereegranskat)abstract
- A frequency domain analysis of a second order Iterative Learning Control (ILC) algorithm is considered. It is shown that an unstable first order ILC can be stabilized by the introduction of a second order term in the ILC. Bounds for stability are presented in the frequency domain for the second order term. The bounds are found using a geometrical approach based on the special structure of the transfer matrix in the iterative system. Two examples are included showing that introducing the higher order ILC can both stabilize an unstable first order ILC algorithm, as well as give better convergence properties compared to using a first order ILC algorithm.
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| 40. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
-
A Frequency Domain Analysis of a Second Order Iterative Learning Control Algorithm
- 1999
-
Ingår i: Proceedings of the 38th IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780352505 ; , s. 1587-1592 vol.2
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A frequency domain analysis method of a second order iterative learning control (ILC) algorithm is considered. Using the notion of iterative systems bounds for stability are presented in the frequency domain for the second order term. The bounds are found using a geometrical approach based on the special structure of the transfer matrix in the iterative system. Two examples are included showing how the analysis method can be used in an application.
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| 41. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
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A General Framework for Iterative Learning Control
- 2002
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Ingår i: Proceedings of the 15th IFAC World Congress. - Linköping : Linköping University Electronic Press. - 9783902661746 ; , s. 224-224
-
Konferensbidrag (refereegranskat)abstract
- In this contribution we place ILC in the realm of numerical optimization. This clarifies the role played by the design variables and how they affect e.g. convergence properties. We give a model based interpretation of these design variables and also a sufficient condition for convergence of ILC which is similar in spirit to the sufficient and necessary condition previously derived for linear systems. This condition shows that the desired performance has to be traded against modelling accuracy. Finally, one of the main benefits of ILC when non-minimum phase systems are concerned, the possibility of non-causal control, is given a comprehensive coverage.
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| 42. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
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A Model Based Iterative Learning Control Method Applied to 3 Axes of a Commercial Industrial Robot
- 2000
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Ingår i: Proceedings of the 6th IFAC Symposium on Robot Control. - 9780080435619
-
Konferensbidrag (refereegranskat)abstract
- A synthesis algorithm for the filters in a first order ILC is presented and applied on an industrial robot. The proposed ILC synthesis method is evaluated using two experiments on the robot. The first is a one-axis experiment where the system can be seen as a single servo. A modeling experiment is done to give input to the synthesis algorithm and then ILC is applied to the single axis showing a dramatic improvement in trajectory following. In the second experiment ILC is applied to a more complex multi axes motion where the robot draws a circle in a plane. The evaluation of the result is done using a pen mounted on the robot and it is evident that also on the arm-side an improved motion can be achieved. In both experiments the error converges to a stable level in about 5 iterations. Since a model is desired for the synthesis, an extra iteration has to be done for the modeling experiment. In this particular case a good path following can therefore be achieved after 6 iterations.
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| 43. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
-
A Model Based Iterative Learning Control Method Applied to an Industrial Robot
- 2000
-
Ingår i: Proceedings of Reglermöte 2000. ; , s. 73-78
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- A synthesis algorithm for the filters in a first order ILC is presented and applied on an industrial robot. The proposed ILC synthesis method is evaluated using two experiments on the robot. The first is a one-axis experiment where the system can be seen as a single servo. A modeling experiment is done to give input to the synthesis algorithm and then ILC is applied to the single axis showing a dramatic improvement in trajectory following. In the second experiment ILC is applied to a more complex multi axes motion where the robot draws a circle in a plane. The evaluation of the result is done using a pen mounted on the robot and it is evident that also on the arm-side an improved motion can be achieved. In both experiments the error converges to a stable level in about 5 iterations. Since a model is desired for the synthesis, an extra iteration has to be done for the modeling experiment. In this particular case a good path following can therefore be achieved after 6 iterations.
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| 44. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
-
A Note on Causal and CITE Iterative Learning Control Algorithms
- 2003
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Time and frequency domain convergence properties of causal and Current Iteration Tracking Error (CITE) discrete time Iterative Learning Control (ILC) algorithms are discussed. Considering necessary and sufcient convergence conditions basic matrix properties can be utilized to show that causal as well as CITE ILC algorithms converge to zero error in only very restrictive special cases. The frequency domain convergence conditions, sucient for monotone convergence, are studied using a discrete-time version of Bode's integral theorem. The result is that causal and CITE ILC algorithms will not satisfy the frequency domain conditions except if the system has relative degree zero or it is accepted that the algorithms do not converge to zero error.
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| 45. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
-
A Note on Causal and CITE Iterative Learning Control Algorithms
- 2005
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Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 41:2, s. 345-350
-
Tidskriftsartikel (refereegranskat)abstract
- The convergence properties of causal and current iteration tracking error (CITE) discrete time iterative learning control (ILC) algorithms are studied using time and frequency domain convergence criteria. Of particular interest are conditions for monotone convergence, and these are evaluated using a discrete-time version of Bode's integral theorem.
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| 46. |
- Norrlöf, Mikael, 1971-
(författare)
-
Adaptive Iterative Learning Control Algorithms for Disturbance Rejection
- 2000
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The disturbance rejection formulation to iterative learning control is discussed and the problem of iterative learning control with measurement disturbance is covered. It is shown that by taking the measurement disturbance into consideration the resulting iterative learning control filters become time varying. To cover the case when the controlled system is non linear, time invariant and/or the disturbance that should be rejected is changing as a function of iteration, an adaptive iterative learning control algorithm is presented. The adaptive algorithm is based on an estimation procedure, using a Kalman filter and a linear quadratic optimal control solution. Results from experiments on an industrial robot show that the algorithm is successful also in an application.
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| 47. |
- Norrlöf, Mikael, 1971-
(författare)
-
An Adaptive Approach to Iterative Learning Control with Experiments on an Industrial Robot
- 2001
-
Ingår i: Proceedings of the 2001 European Control Conference. - Linköping : Linköping University Electronic Press. ; , s. 220-225
-
Konferensbidrag (refereegranskat)abstract
- An adaptive approach to Iterative Learning Control (ILC) based on Kalman filters and optimization of a quadratic criterion is presented. The idea is to estimate one of the design parameters in the Kalman filter and hence create an adaptive gain in the ILC updating formula. The proposed ILC design is compared with two other ILC schemes and they are all implemented on an industrial robot. The results show that the proposed adaptive ILC scheme is fast, and also robust since the gain is reduced as the error is decreased.
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| 48. |
- Norrlöf, Mikael, 1971-
(författare)
-
An Adaptive Iterative Learning Control Algorithm with Experiments on an Industrial Robot
- 2002
-
Ingår i: IEEE transactions on robotics and automation. - Linköping : Linköping University Electronic Press. - 1042-296X. ; 18:2, s. 245-251
-
Tidskriftsartikel (refereegranskat)abstract
- An adaptive iterative learning control (ILC) algorithm based on an estimation procedure using a Kalman filter and an optimization of a quadratic criterion is presented. It is shown that by taking the measurement disturbance into consideration the resulting ILC filters become iteration-varying. Results from experiments on an industrial robot show that the algorithm is successful also in an application.
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| 49. |
- Norrlöf, Mikael, 1971-, et al.
(författare)
-
An ILC approach to feed-forward friction compensation
- 2020
-
Ingår i: Proceedings of the 21st IFAC World Congress. - : Elsevier. ; , s. 1409-1414
-
Konferensbidrag (refereegranskat)abstract
- An iterative, learning based, feed-forward method for compensation offriction in industrial robots is studied. The method is put into an ILC framework by using a two step procedure proposed inliterature. The friction compensation method is based on ablack-box friction model which is learned from operational data,and this can be seen as the first step in the method. In the second step the learned model is usedfor compensation of the friction using the reference joint velocityas input. The approach is supported by simulation experiments.
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| 50. |
- Norrlöf, Mikael, 1971-
(författare)
-
Analysis of a Second Order Iterative Learning Control Algorithm
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In the report aspects on stability, performance, and robustness is discussed for general second order methods. The basis for the analysis is linear iterative systems which are also covered in the report. The behavior of second order ILC systems is discussed both from a transient as well as an asymptotic point of view. Two different design algorithms are proposed and analyzed theoretically. The two algorithms are then compared with a first order ILC design in an experiment on an industrial robot from ABB Robotics. The result is that the second order ILC designs compete well with the first order design but does not prove to be better, either from a performance nor from a robustness perspective.
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