Iterative learning control for a class of nonlinear systems

Author

Dong, Shen ; Hanfu, Chen

Author_Institution

Key Lab. of Syst. & Control, Chinese Acad. of Sci., Beijing

fYear

2008

fDate

16-18 July 2008

Firstpage

60

Lastpage

64

Abstract

The iterative learning control (ILC) is derived for a class of nonlinear systems and is proved to converge to the desired control with probability one, minimizing some performance index. The state equation is nonlinear and the observation equation is with noise. The control sequence does not directly feed to the system but first passes through a nonlinear function such as the dead-zone, pre-load, and saturation etc. Then the outputs of these nonlinearities linearly input to the system.

Keywords

control nonlinearities; iterative methods; learning systems; nonlinear control systems; nonlinear functions; performance index; control sequence; iterative learning control; nonlinear function; nonlinear systems; nonlinearities; observation equation; performance index; state equation; Control nonlinearities; Control systems; Feeds; Laboratories; Nonlinear control systems; Nonlinear equations; Nonlinear systems; Performance analysis; Stochastic resonance; Dead-zone; Iterative learning control; Pre-load; Saturation; Stochastic approximation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2008. CCC 2008. 27th Chinese

Conference_Location

Kunming

Print_ISBN

978-7-900719-70-6

Electronic_ISBN

978-7-900719-70-6

Type

conf

DOI

10.1109/CHICC.2008.4605418

Filename

4605418