Title

Designing Of Guaranteed Cost Iterative Learning Algorithms Based On Lmi Method

Keywords

Guaranteed cost iterative learning algorithms; Iteration domain; Iterative learning control; Linear quadratic performance function

Abstract

Performance function based iterative learning algorithms are investigated in this paper. At first, a linear quadratic performance function is denned in iteration domain, then an optimal iterative learning algorithm is presented for linear discrete-time systems, and a guaranteed cost iterative learning algorithm and its optimization are developed for linear discrete-time systems with uncertainties. In these algorithms, the convergence speed can be adjusted easily just by the parameters in the performance function, and the designing and optimization of the guaranteed cost iterative learning algorithm are linear matrix inequalities (LMI) based, so can be realized easily using Matlab Toolbox.

Publication Date

7-1-2006

Publication Title

Zidonghua Xuebao/Acta Automatica Sinica

Volume

32

Issue

4

Number of Pages

578-585

Document Type

Article

Personal Identifier

scopus

Socpus ID

33748471522 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33748471522

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