DocumentCode :
3317547
Title :
The convergence of parameter estimates is not necessary for a general self-tuning control system- stochastic plant
Author :
Zhang, Weicun
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. Beijing, Beijing, China
fYear :
2009
fDate :
15-18 Dec. 2009
Firstpage :
3489
Lastpage :
3494
Abstract :
This paper is concerned with the stability and convergence of a general stochastic self-tuning control (STC) system, which consists of arbitrary control strategy and arbitrary estimation algorithm. The necessary conditions required for global stability and convergence are relaxed, i.e., the convergence of parameter estimates is removed. The key point is that with the help of virtual equivalent system (VES) concept, the original nonlinear dominant (nonlinear in structure) problem of stochastic STC is converted to a linear dominant (linear in structure) problem - stochastic slow switching control system.
Keywords :
parameter estimation; self-adjusting systems; stability; stochastic systems; arbitrary estimation algorithm; general stochastic self-tuning control system; global stability; nonlinear dominant problem; parameter estimation convergence; self-tuning control system; stochastic plant; stochastic slow switching control system; virtual equivalent system; Adaptive control; Algorithm design and analysis; Control systems; Convergence; Nonlinear control systems; Parameter estimation; Recursive estimation; Stability; Stochastic resonance; Stochastic systems; convergence; slow switching; stability; stochastic self-tuning control; virtual equivalent system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
ISSN :
0191-2216
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2009.5400884
Filename :
5400884
Link To Document :
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