Constrained predictive control based on T-S fuzzy model for nonlinear systems |
| |
作者单位: | Su Baili(Dept. of Automation, Nankai Univ., Tianjin 300071, P. R. China;Qufu Normal Univ., Qufu 273165, P. R. China) ;
Chen Zengqiang(Dept. of Automation, Nankai Univ., Tianjin 300071, P. R. China) ;
Yuan Zhuzhi(Dept. of Automation, Nankai Univ., Tianjin 300071, P. R. China) ; |
| |
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.
|
关 键 词: | 非线性系统 T-S模糊模型 约束预测控制 广义预测控制 模糊集 |
收稿时间: | 7 July 2005. |
Constrained predictive control based on T-S fuzzy model for nonlinear systems |
| |
Authors: | Su Baili Chen Zengqiang Yuan Zhuzhi |
| |
Institution: | 1. Dept. of Automation, Nankai Univ., Tianjin 300071, P. R. China;Qufu Normal Univ., Qufu 273165, P. R. China 2. Dept. of Automation, Nankai Univ., Tianjin 300071, P. R. China |
| |
Abstract: | 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 orthogonal least 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. |
| |
Keywords: | Generalized predictive control (GPC) Nonlinear system T-S fuzzy model Input constraint Fuzzy cluster |
本文献已被 维普 万方数据 ScienceDirect 等数据库收录! |
| 点击此处可从《系统工程与电子技术(英文版)》浏览原始摘要信息 |
| 点击此处可从《系统工程与电子技术(英文版)》下载免费的PDF全文 |