Title :
Robust identification of fuzzy model on H∞ error estimation
Author :
Wang, Hongwei ; Wang, Jia ; Gu, Hong
Author_Institution :
Sch. of Control Sci. & Eng., Dalian Univ. of Technol., Dalian, China
Abstract :
The paper proposes a new fuzzy identification method based on H∞ error estimation for the issues of robust identification of fuzzy model. The H∞ state estimation is applied to the parameter identification of fuzzy model in the paper. The presented algorithm not only guarantees to satisfy a specified level of robustness, and also provides an optimized error upper bound. Finally, we study the fuzzy model of nonlinear system. With the comparison between fuzzy identification based on recursive least square and the proposed algorithm in the paper, the simulated results show that the improving robustness of identification needs to be at the cost of approximation accuracy of identification.
Keywords :
H∞ optimisation; approximation theory; error analysis; fuzzy systems; least squares approximations; nonlinear control systems; recursive estimation; robust control; H∞ error estimation; approximation accuracy; fuzzy identification; nonlinear system; optimisation; recursive least square algorithm; robust identification; robustness; Control systems; Error analysis; Estimation; Filtering; Least squares approximation; Robustness; Uncertainty; H∞ estimation; fuzzy clustering; fuzzy model; robustness; system identification;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554699
