Constrained predictive control based on T-S fuzzy model for nonlinear systems  

作　　者：Su Baili Chen Zengqiang Yuan Zhuzhi 

机构地区：[1]Dept. of Automation, Nankai Univ., Tianjin 300071, P. R. China [2]Qufu Normal Univ., Qufu 273165, P. R. China

出　　处：《Journal of Systems Engineering and Electronics》2007年第1期95-100,共6页系统工程与电子技术（英文版）

基　　金：This Project was supported by the National Natural Science Foundation of China (60374037 and 60574036);the Opening Project Foundation of National Lab of Industrial Control Technology (0708008).

摘　　要：A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.

关 键 词：Generalized predictive control （GPC） Nonlinear system T-S fuzzy model Input constraint Fuzzy cluster 

分 类 号：O231.2[理学—运筹学与控制论]