Title :
A robust adaptive control system for poorly known large dimension plants
Author_Institution :
Dept. of Mech. Eng., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil
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;
Conference_Titel :
Circuits and Systems, 1996., IEEE 39th Midwest symposium on
Conference_Location :
Ames, IA
Print_ISBN :
0-7803-3636-4
DOI :
10.1109/MWSCAS.1996.593138
