Title :
Markov parameter estimation for stochastic continuous systems via Legendre polynomials
Author_Institution :
Wuhan Iron & Steel Univ., Wuhan, China
fDate :
29 June-1 July 1994
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;
Conference_Titel :
American Control Conference, 1994
Print_ISBN :
0-7803-1783-1
DOI :
10.1109/ACC.1994.752315
