Norm-Optimal Iterative Learning Control With Intermediate Point Weighting: Theory, Algorithms, and Experimental Evaluation

Author

Owens, David H. ; Freeman, C.T. ; Thanh Van Dinh

Author_Institution

Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK

Volume

21

Issue

3

fYear

2013

fDate

May-13

Firstpage

999

Lastpage

1007

Abstract

This brief considers the iterative learning control (ILC) problem when tracking is only required at a subset of isolated time points along the trial duration. It presents a norm-optimal ILC solution to the problem with well-defined convergence properties, design guidelines, and supporting experimental results using an electromechanical test facility.

Keywords

control system synthesis; convergence; iterative methods; learning systems; optimal control; tracking; ILC problem; convergence properties; design guideline; electromechanical test facility; intermediate point weighting; isolated time point; norm-optimal ILC solution; norm-optimal iterative learning control; tracking; Convergence; Eigenvalues and eigenfunctions; Equations; Feedforward neural networks; Frequency modulation; Hilbert space; State feedback; Iterative learning control (ILC); iterative methods; learning control systems; linear systems; motion control; non-minimum phase systems; optimization methods; test facilities;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/TCST.2012.2196281

Filename

6200836