Title :
Separable gradient estimation algorithm for Hammerstein systems based on decompositions
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
This paper studies parameter estimation problem of Hammerstein systems by using the gradient search principle. The Hammerstein system is a bilinear-parameter system which is linear about two parameter vectors, respectively. A separable gradient algorithm is developed for estimating the two parameter vectors based on the hierarchical identification principle. The algorithm is simple in principle and easy to implement online. The simulation results test the effectiveness of the proposed algorithm.
Keywords :
bilinear systems; gradient methods; nonlinear control systems; parameter estimation; search problems; Hammerstein systems; bilinear-parameter system; decompositions; gradient search principle; hierarchical identification principle; nonlinear systems; parameter estimation problem; parameter vector estimation; separable gradient estimation algorithm; Convergence; Estimation; Iterative methods; Parameter estimation; Signal processing algorithms; Stochastic processes; Vectors;
Conference_Titel :
American Control Conference (ACC), 2012
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4577-1095-7
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2012.6315354
