A multivariable generalized predictive control approach based on T–S fuzzy model

Article type: Research Article

Authors: Huaguang, Zhang^; | Cai, Lilong | Bien, Zeungnam

Affiliations: Department of Automatic Control, Northeastern University, Shenyang 110006, P.R. China. E-mail: hg_zhang@21cn.com | Department of Mechanical Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong. E-mail: melcai@uxmail.ust.hk | Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Kusong-dong, Yusong-Ku, Taejon, 305-701, Korea. E-mail: zbien@ee.kaist.ac.kr

Note: [] Corresponding author.

Abstract: In this paper, the Takagi–Sugeno (T–S) fuzzy model is used to express dynamic systems, and an on-line identification algorithm for its parameters and structures is presented. A new multivariable fuzzy generalized predictive control approach is put forward based on the identified fuzzy model by means of Clark's principle of single-variable generalized predictive control, some of whose performances are analysed in detail. A simulation study of the multivariable load system of electric generating unit shows that the approach is superior to conventional load control systems.

Journal: Journal of Intelligent and Fuzzy Systems, vol. 9, no. 3-4, pp. 169-189, 2000