An adaptive discrete-time ILC strategy using fuzzy systems for iteration-varying reference trajectory tracking

• Published in: International journal of control, automation, and systems Vol. 13; no. 1; pp. 222 - 230
• Main Authors: Xiao, Teng-Fei, Li, Xiao-Dong, Ho, John K. L.
• Format: Journal Article
• Language: English
• Published: Heidelberg Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.02.2015; Springer Nature B.V; 제어·로봇·시스템학회
• Subjects: Adaptive algorithms; Adaptive systems; Algorithms; Analysis; Approximation; Control; Control systems; Design; Dynamical systems; Engineering; Fuzzy logic; Fuzzy systems; Mechatronics; Regular Paper; Robotics; Strategy; Studies; System theory; Telematics; Tracking; Trajectories; 제어계측공학; Discrete-time systems; iteration-varying reference trajectory; fuzzy systems; iterative learning control
• ISSN: 1598-6446; 2005-4092
• DOI: 10.1007/s12555-013-0474-1

In this article, a novel fuzzy systems based on adaptive Iterative Learning Control (ILC) strategy is presented to deal with a class of non-parametric nonlinear discrete-time systems which perform iteration-varying reference trajectory tracking. Using the technique of fuzzy systems to compensate for the non-parametric uncertainty of the discrete-time system dynamics, the proposed adaptive ILC scheme can well track the iteration-varying reference trajectory beyond the initial time points. The convergence of the fuzzy systems based adaptive ILC algorithm is guaranteed by theoretical analysis, and a numerical example is given to illustrate the effectiveness of the adaptive ILC scheme.