DocumentCode :
3469187
Title :
Multi-Innovation Gradient Parameter Estimation Based Adaptive Control for Discrete-Time Systems
Author :
Zhang, Jiabo ; Ding, Feng ; Shi, Yang
Author_Institution :
Jiangnan (Southern Yangtze) Univ., Wuxi
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
399
Lastpage :
404
Abstract :
This paper uses the multi-innovation stochastic gradient (MISG) algorithm to estimate the parameters of discrete- time systems and presents an MISG based adaptive control scheme. Further, we prove that the parameter estimation error converges to zero under the persistent excitation, and the parameter estimation based control algorithm can achieve virtually asymptotically optimal control and ensure that the closed-loop systems are stable and globally convergent. The simulation results are included.
Keywords :
adaptive control; asymptotic stability; closed loop systems; convergence; discrete time systems; gradient methods; optimal control; parameter estimation; stochastic processes; adaptive control; closed-loop systems; discrete-time systems; multiinnovation stochastic gradient algorithm; parameter estimation; persistent excitation; stability; virtually asymptotically optimal control; Adaptive control; Control systems; Convergence; Equations; Error correction; Optimal control; Parameter estimation; Polynomials; Stochastic processes; Stochastic systems; System identification; adaptive control; parameter estimation; stochastic gradient;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4338595
Filename :
4338595
Link To Document :
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