Title :
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
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;
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
DOI :
10.1109/CHICC.2008.4605418
