LMI-based fuzzy controller design with minimum upper bound input energy and state variance constraints for discrete fuzzy stochastic systems

Article type: Research Article

Authors: Chang, Wen-Jer | Shing, Chong-Cheng

Affiliations: Department of Marine Engineering, National Taiwan Ocean University, Keelung 202, Taiwan | Institute of Electrical and Control Engineering, National Chiao Tung University, Hsinchu 300, Taiwan

Note: [] Corresponding author. Tel.: +886 2 2462 2192 Ext. 7110; Fax: +886 2 2463 3765; E-mail: [email protected]

Abstract: In this paper, a fuzzy controller design problem is considered for the discrete-time Takagi-Sugeno (T-S) fuzzy stochastic systems. The main purpose of this paper is to provide a systematic fuzzy controller design procedure for the discrete-time nonlinear stochastic systems, which are modeled by the T-S type fuzzy systems. A methodology is developed to find the discrete-time fuzzy controllers for minimizing upper bound control input energy and achieving state variance constraints for discrete-time T-S fuzzy stochastic systems. It is shown that the present approach can be used to solve the linear feedback control gains for each rule of the T-S fuzzy controllers using the Linear Matrix Inequality (LMI) technique. Finally, we apply the proposed controller design method to control a truck-trailer system to show the utility of the present approach.

Keywords: discrete-time takagi-sugeno fuzzy models, upper bound input energy, state variance constraints, linear matrix inequalities

Journal: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 2, pp. 115-124, 2004