An initial state learning method for iterative learning control of uncertain time-varying systems

2002 ◽  
Author(s):  
Yangquan Chen ◽  
Changyun Wen ◽  
Jian-Xin Xu ◽  
Mingxuan Sun
Keyword(s):  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Time Varying ◽  
Learning Method ◽  
Initial State ◽  
Time Varying Systems ◽  
State Learning ◽  
Uncertain Time

An iterative learning control algorithm based on time varying pilot factor

2019 ◽  
Vol 25 (8) ◽  
pp. 1484-1491 ◽  
Author(s):  
Jing Huang ◽  
Zhenxiang Xu ◽  
Guoxiu Li ◽  
Cheng Qiu ◽  
Haitao Huang
Keyword(s):  
Control System ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Sufficient Conditions ◽  
Learning Control ◽  
Critical Issue ◽  
Iterative Learning ◽  
Time Varying ◽  
Initial State ◽  
Hydraulic Servo

Owing to the control system being repetitive and nonlinear, a time-varying pilot factor control algorithm based on iterative learning control is proposed. The convergence of the TPF-ILC control algorithm is mathematically proven and the sufficient conditions are given. Thereafter, the initial state issue of iterative learning is explored, which is the critical issue of iterative learning control. The convergence of the system’s control error and the initial state of every single period have been mathematically proved by using continuous and repetitive properties of the system, even if the initial states of every single iterative learning period are not strictly the same. At the end of this paper, the TPF-ILC algorithm is applied in a hydraulic servo control system, and experimental results indicate the effectiveness and practicability of the TPF-ILC algorithm.

Sign in / Sign up

Export Citation Format

Share Document