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.
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).
作者简介
Su Baili was born in 1971. She received her B. S. and M. S. Degrees from Qufu Normal University respectively in 1993 and 1998. Now she is a Ph.D candidate in Nankai University. Her main research interests are predictive control and fuzzy control. E-mail： subaili111@ 126.comChen Zengqiang was bom in 1964. He received his B. S. degree of Mathematics from Nankai University in 1987. And he received his M. S. and Ph.D. degrees of Control Theory and Control Engineering from Nankai University respectively in 1990 and 1997. Now he is a professor and Ph.D. advisor in Department of Automation, Nankai University. His main research interests are adaptive control, predictive control and intelligence control. E-mail： chenzq@nankai.edu.cnYuan Zhuzhi was born in 1937. He graduated from Department of Mathematics of Nankai University in 1962. Now he is a professor and Ph.D. advisor in Department of Automation, Nankai University. His current research interests include adaptive control, predictive control and intelligence control. E-mail： yuanzhzh@nankai.edu.cn
