Title :
Identification of Hammerstein MIMO systems using the key-term separation principle
Author :
Qianyan Shen ; Feng Ding
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
This paper focuses on parameters estimation problems of multivariable nonlinear systems. A hierarchical least squares algorithm is proposed by using key-term separation principle and hierarchical identification principle. The algorithm has lower computational load than the existing over-parametrization methods. Finally, a numerical example is given to show the effectiveness of the proposed algorithm.
Keywords :
MIMO systems; least squares approximations; multivariable control systems; nonlinear control systems; parameter estimation; Hammerstein MIMO systems identification; computational load; hierarchical identification principle; hierarchical least squares algorithm; key-term separation principle; multivariable nonlinear systems; over-parametrization methods; parameters estimation problems; Computational modeling; Heuristic algorithms; MIMO; Mathematical model; Noise; Parameter estimation; Vectors; Hierarchical identification; Key-term separation; Least squares; Multivariable system; Parameter identification;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053237
