DocumentCode :
1938592
Title :
Achieving optimality in adaptive control: the “bet on the best” approach
Author :
Campi, M.C.
Author_Institution :
Dept. of Electr. Eng. & Autom., Brescia Univ., Italy
Volume :
5
fYear :
1997
fDate :
10-12 Dec 1997
Firstpage :
4671
Abstract :
Over the last two decades, the certainty equivalence principle has been the fundamental paradigm in the design of adaptive control laws. It is well known, however, that for general control criterions the performance achieved through its use is strictly suboptimal. In this paper, we introduce a new general philosophy based on the certainty equivalence idea-so as to ensure optimality in adaptive control problems under general conditions. Rather than focusing on a particular control scheme, we present the method in a general control setting. Specific control algorithms to cope with different situations can be derived from this general method
Keywords :
adaptive control; least squares approximations; linear quadratic Gaussian control; parameter estimation; probability; stochastic systems; adaptive control; certainty equivalence principle; least squares estimation; linear quadratic Gaussian control; long term average cost; optimal control; probability; stochastic systems; Adaptive control; Automatic control; Automation; Control systems; Cost function; Least squares methods; Optimal control; Parameter estimation; Signal processing algorithms; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
ISSN :
0191-2216
Print_ISBN :
0-7803-4187-2
Type :
conf
DOI :
10.1109/CDC.1997.649725
Filename :
649725
Link To Document :
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