scholarly journals An Iterative Learning Control Design Method for Nonlinear Discrete-Time Systems with Unknown Iteration-Varying Parameters and Control Direction

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Duo Zhao ◽  
Yong Yang
Keyword(s):  
Discrete Time ◽  
Iterative Learning Control ◽  
Design Method ◽  
Learning Control ◽  
Convergence Condition ◽  
Iterative Learning ◽  
Unknown Parameters ◽  
Varying Parameters ◽  
Control Direction ◽  
And Control

An iterative learning control (ILC) scheme is designed for a class of nonlinear discrete-time dynamical systems with unknown iteration-varying parameters and control direction. The iteration-varying parameters are described by a high-order internal model (HOIM) such that the unknown parameters in the current iteration are a linear combination of the counterparts in the previous certain iterations. Under the framework of ILC, the learning convergence condition is derived through rigorous analysis. It is shown that the adaptive ILC law can achieve perfect tracking of system state in presence of iteration-varying parameters and unknown control direction. The effectiveness of the proposed control scheme is verified by simulations.

An Iterative Learning Control for Uncertain Systems Using Structured Singular Value

1999 ◽  
Vol 121 (4) ◽  
pp. 660-667 ◽  
Author(s):  
Tae-Yong Doh ◽  
Jung-Ho Moon ◽  
Myung Jin Chung
Keyword(s):  
Robust Stability ◽  
Iterative Learning Control ◽  
Design Method ◽  
Learning Control ◽  
Convergence Condition ◽  
Singular Value ◽  
Iterative Learning ◽  
Structured Singular Value ◽  
Plant Uncertainty ◽  
Uncertain Linear Systems

To deal with an iterative learning control (ILC) system with plant uncertainty, a set of new terms related with robust convergence is first defined. This paper proposes a sufficient condition for not only robust convergence but also robust stability of ILC for uncertain linear systems, including plant uncertainty. Thus, to find a new condition unrelated to the uncertainty, we first separate it into a known part and uncertainty one using linear fractional transformations (LFTs). Then, robust convergence and robust stability of an ILC system is determined by structured singular value (μ) of only the known part. Based on the novel condition, a learning controller and a feedback controller are developed at the same time to ensure robust convergence and robust stability of the ILC system under plant uncertainty. Lastly, the feasibility of the proposed convergence condition and design method are confirmed through computer simulation on an one-link flexible arm.

Iterative Learning Control for a Class of Linear Discrete-time Switched Systems

2014 ◽  
Vol 39 (9) ◽  
pp. 1564-1569 ◽  
Author(s):  
Xu-Hui BU ◽  
Fa-Shan YU ◽  
Zhong-Sheng HOU ◽  
Fu-Zhong WANG
Keyword(s):  
Discrete Time ◽  
Switched Systems ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning
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