A robust adaptive control system for poorly known large dimension plants

Author

Gálvez, J.M.

Author_Institution

Dept. of Mech. Eng., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil

Volume

3

fYear

1996

fDate

18-21 Aug 1996

Firstpage

1248

Abstract

This paper presents a model reference adaptive controller for poorly known systems. The control algorithm is based on the concept of pole dominance in the frequency domain. Conditions for asymptotic stability are established without constraining the plant to be strictly positive real (SPR). It is shown that the proposed Dynamic Model Reduction (DMR) scheme is asymptotic stable inside of a relatively large neighborhood of the nominal plant dynamics. Simulation results illustrate the regulation and tracking outstanding performances of the proposed scheme

Keywords

asymptotic stability; frequency-domain analysis; model reference adaptive control systems; pole assignment; reduced order systems; robust control; uncertain systems; algorithm; asymptotic stability; direct model reference adaptive control; dynamic model reduction; frequency domain; pole dominance; poorly known large dimension plant; regulation; robust system; simulation; tracking; Adaptive control; Asymptotic stability; Frequency domain analysis; Mechanical engineering; Nonlinear control systems; Programmable control; Read only memory; Reduced order systems; Robust control; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996., IEEE 39th Midwest symposium on

Conference_Location

Ames, IA

Print_ISBN

0-7803-3636-4

Type

conf

DOI

10.1109/MWSCAS.1996.593138

Filename

593138