DocumentCode
335401
Title
Markov parameter estimation for stochastic continuous systems via Legendre polynomials
Author
Zhao, Mingwang
Author_Institution
Wuhan Iron & Steel Univ., Wuhan, China
Volume
2
fYear
1994
fDate
29 June-1 July 1994
Firstpage
1497
Abstract
Firstly the least squares (LS) estimation method for stochastic continuous systems disturbed by Wiener process is studied via Legendre polynomials. Secondly, the correlativeness of the approximating values of Wiener process is discussed,then, an unbiased consistent Markov method with the minimum covariance is given. Finally, a simulation shows the effectiveness of these methods.
Keywords
Legendre polynomials; Markov processes; least squares approximations; parameter estimation; stochastic processes; stochastic systems; Legendre polynomials; Markov parameter estimation; Wiener process; correlativeness; least squares estimation; minimum covariance; stochastic continuous systems; unbiased consistent Markov method; Continuous time systems; Equations; Function approximation; Iron; Least squares approximation; Linear systems; Parameter estimation; Polynomials; Steel; Stochastic systems;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1994
Print_ISBN
0-7803-1783-1
Type
conf
DOI
10.1109/ACC.1994.752315
Filename
752315
Link To Document