Iterative learning control for a class of uncertain nonlinear systems with current state feedback

Abstract

In this paper, the problem of iterative learning control is addressed for a class of uncertain nonlinear systems with unknown input–output coupling parameters. Firstly, we prove that the control system is realisable if and only if all the input–output coupling parameters are nonzero. Secondly, to surmount the obstacle arising from the unknown input–output coupling parameters, a learning based identification technique is developed for the unknown input–output coupling parameters. Thirdly, a control protocol composed of iterative learning control update law and current state feedback is proposed for the controlled system. The findings suggest that the state feedback part does not change the realizability of controlled system and can be used to improve the transient tracking performance. Especially under certain condition, it can guarantee the monotone convergence of ILC process. Finally, simulation examples are provided to illustrate the effectiveness of the proposed control protocol.

Keywords:

• Iterative learning control
• uncertain nonlinear systems
• current state feedback
• identification technique
• unknown input–output coupling parameter

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Jian Liu http://orcid.org/0000-0002-7094-5726

Additional information

Funding

This work is supported by the National Natural Science Foundation of China [grant numbers 61803291 and 61773301], and by the Fundamental Research Funds for the Central Universities [grant number JB180405].