Internal model-based robust iterative learning control for uncertain LTI systems

Author

Tayebi, Abdelhamid ; Zaremba, Marek B.

Author_Institution

Dept. of Electr. Eng., Lakehead Univ., Thunder Bay, Ont., Canada

Volume

4

fYear

2000

fDate

2000

Firstpage

3439

Abstract

Investigates the combination of an iterative learning control (ILC) with an internal model control (IMC) for uncertain linear time-invariant (LTI) systems. The convergence of the iterative process is investigated and reformulated as a general robust control problem. For a certain choice of the IMC and ILC filters, we prove that the condition of convergence to zero of the iterative process is nothing but the robust performance condition of the IMC structure. Using the general robust control formulation, we propose a design procedure for the ILC-IMC filters using the μ-synthesis approach

Keywords

convergence; filtering theory; learning systems; linear systems; model reference adaptive control systems; robust control; uncertain systems; μ-synthesis approach; design procedure; internal model-based robust iterative learning control; linear time-invariant systems; robust performance condition; uncertain LTI systems; Automatic control; Automatic generation control; Control systems; Convergence; Filters; Intelligent robots; Iterative methods; Open loop systems; Robust control; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2000. Proceedings of the 39th IEEE Conference on

Conference_Location

Sydney, NSW

ISSN

0191-2216

Print_ISBN

0-7803-6638-7

Type

conf

DOI

10.1109/CDC.2000.912235

Filename

912235