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Multiple model iterative learning control
Neurocomputing, 2010Iterative learning controller (ILC), which is based on the model of the system, can give good performance in the steady state if the input is updated from trial to trial. The model, on which the ILC is set up, is not always needed to be exact. But a better model will lead to the deduction of iteration times.
Xiaoli Li 0011, Wen Zhang
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Predictive gradient iterative learning control
2015 54th IEEE Conference on Decision and Control (CDC), 2015Iterative learning control (ILC) is a control design method for high performance trajectory tracking. Most existing results achieve this by learning from information collected over past executions of the task (named trials). This paper proposes a novel gradient based ILC design which updates the control input by learning not only from past trials but ...
Bing Chu +2 more
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An algebraic approach to iterative learning control
Proceedings of the IEEE Internatinal Symposium on Intelligent Control, 2003In this paper discrete-time iterative learning control (ILC) systems are analysed from an algebraic point of view. The algebraic analysis shows that an ILC synthesis problem can be considered as a tracking problem of a multi-channel step-function. Furthermore, the plant to be controlled is a static multivariable plant.
Jari J. Hätönen +2 more
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The influence of disturbances in iterative learning control
Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005., 2005For systems that perform repetitive tasks, a high performance feedforward signal can be derived using Iterative Learning Control (ILC). The feedforward signal is updated through successive iterations. Disturbances present in the control scheme, such as load and measurement disturbances, are also present in the learning process and deteriorate the ...
Roel J. E. Merry +2 more
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Discrete-Time Iterative Learning Control
2015© Springer Science+Business Media Singapore 2015. In this study the convergence properties of iterative learning control (ILC) algorithms are discussed. 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.
Abidi K, Xu J-X
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An iterative learning control scheme for manipulators
Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97, 2002This paper presents an iterative learning control scheme for high-geared industrial manipulators that perform repeated tasks. The input update law of the iterative learning control is given in the frequency domain, together with a sufficient condition for convergence of the iterative process.
Jung-Ho Moon +2 more
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An iterative learning control of robot manipulators
IEEE Transactions on Robotics and Automation, 1991An iterative learning scheme comprising a unique feedforward learning controller and a linear feedback controller is presented. In the feedback loop, the fixed-gain PD controller provides a stable open neighborhood along a desired trajectory. In the feedforward path, on the other hand, a learning control strategy is exploited to predict the desired ...
KUC, TY, LEE, JS, NAM, KH
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1996
Abstract A theory of iterative learning control for refinement of motions of robotic systems is presented, together with simulation results. It is shown that the passivity of such non-linear mechanical systems plays a key role in the ability to acquire a desired and skilled movement through repeated practice.
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Abstract A theory of iterative learning control for refinement of motions of robotic systems is presented, together with simulation results. It is shown that the passivity of such non-linear mechanical systems plays a key role in the ability to acquire a desired and skilled movement through repeated practice.
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Iterative learning control with saturation constraints
2009 American Control Conference, 2009We consider the problem of synthesis of iterative learning control schemes for linear systems with saturation constraints. The problem of minimizing the tracking error is formulated as a constrained convex optimization problem, namely a linearly constrained quadratic program.
Sandipan Mishra +2 more
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Harnessing the nonrepetitiveness in iterative learning control
Proceedings of the 41st IEEE Conference on Decision and Control, 2002., 2003In iterative learning control (ILC), it is usually assumed that the disturbances, uncertainties and the desired trajectories are invariant with respect to the iteration number or iteration-independent. In practice, this may not be true. How to accommodate the iteration-dependent disturbances, uncertainties and the desired trajectories is practically ...
YangQuan Chen, Kevin L. Moore 0001
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