Results 321 to 330 of about 816,103 (361)

Fault Tolerant Nonrepetitive Trajectory Tracking for MIMO Output Constrained Nonlinear Systems Using Iterative Learning Control

IEEE Transactions on Cybernetics, 2019
Most works on iterative learning control (ILC) assume identical reference trajectories for the system state over the iteration domain. This fundamental assumption may not always hold in practice, where the desired trajectories or control objectives may ...
Xu Jin
semanticscholar   +1 more source

Predictive gradient iterative learning control

2015 54th IEEE Conference on Decision and Control (CDC), 2015
Iterative 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, David H. Owens 0001, Christopher T. Freeman   +2 more
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High-Precision Tracking of Piezoelectric Actuator Using Iterative Learning Control and Direct Inverse Compensation of Hysteresis

IEEE transactions on industrial electronics (1982. Print), 2019
Rate-dependent hysteretic nonlinearity, which is an inherent characteristic of piezoelectric actuators (PEAs), causes a significant challenge in precise motion control of piezoelectric nanopositioning stages.
Yupei Jian, Deqing Huang, Jiabin Liu, Da Min   +3 more
semanticscholar   +1 more source

An algebraic approach to iterative learning control

Proceedings of the IEEE Internatinal Symposium on Intelligent Control, 2003
In 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, Kevin L. Moore 0001, David H. Owens 0001   +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., 2005
For 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, René van de Molengraft, Maarten Steinbuch   +2 more
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Adaptive Iterative Learning Control for High-Speed Train: A Multi-Agent Approach

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019
The precise tracking control of high-speed train is an essential prerequisite to ensure the safety and comfort of the train. In this paper, an adaptive iterative learning control (ILC) scheme for the velocity and displacement tracking of high-speed train
Deqing Huang, Yong Chen, De-yuan Meng, P. Sun   +3 more
semanticscholar   +1 more source

Iterative learning control with saturation constraints

2009 American Control Conference, 2009
We 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, Ufuk Topcu, Masayoshi Tomizuka   +2 more
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Harnessing the nonrepetitiveness in iterative learning control

Proceedings of the 41st IEEE Conference on Decision and Control, 2002., 2003
In 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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Iterative learning control in feedback systems

Automatica, 1995
A new iterative learning control scheme is presented to provide tracking control for a class of nonlinear systems. The scheme uses a standard feedback control configuration, but is augmented by a feedforward term that is updated via iterative learning control.
Tae-Jeong Jang, Chong-Ho Choi, Hyun-Sik Ahn   +2 more
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Iterative Learning Control

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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