Iterative learning control with an optimality criterion

Author

Liu, Shan ; Wu, Tiejun

Author_Institution

Nat. Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China

Volume

1

fYear

2002

fDate

2002

Firstpage

621

Abstract

An improved iterative learning control based on optimality criterion is proposed in this paper. The control signal in each trial is calculated as the solution of a minimum norm optimization problem with a reasonable performance index. The convergence of the tracking error sequence and input sequence can be proved by the properties of optimality criterion instantly. The iterative learning control algorithm of linear time-varying system assures that the input sequence will converge to the optimal control of linear quadratic tracking problem. The algorithm achieves an exponential rate of convergence. The theory of the proposed algorithm is verified through the comparison in the simulation studies.

Keywords

convergence; intelligent control; linear quadratic control; linear systems; optimal control; optimisation; performance index; time-varying systems; tracking; convergence; iterative learning control; linear quadratic control; linear system; minimum norm optimization; optimal control; optimality criterion; performance index; time-varying system; tracking; Control systems; Industrial control; Iterative algorithms; Laboratories; Optimal control; Performance analysis; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on

Print_ISBN

0-7803-7268-9

Type

conf

DOI

10.1109/WCICA.2002.1022186

Filename

1022186