基于T-S模糊模型的CSTR系统广义预测控制

Generalized Predictive Control of CSTR System Based on T-S Fuzzy Model

模糊预测控制将模糊与预测2种思想相结合,已经成功应用于工控领域。连续搅拌反应釜是化工生产过程中典型的非线性系统,传统控制方法难以满足其控制精度要求。本文提出一种模糊广义预测控制方法。采用改进的模糊划分聚类算法对T-S模糊模型的前件参数进行辨识,仿真证明该算法的辨识效果优于原始模糊聚类算法;结合带有遗忘因子的递推最小二乘法对模糊模型的后件参数进行辨识。采用广义预测控制算法与PID算法分别对连续搅拌反应釜系统进行仿真验证,仿真结果证明了本文方法的有效性。

Fuzzy predictive control combines both fuzzy and predictive ideas and has been successfully applied in the field of industrial control.The continuous stirred tank reactor(CSTR) is a typical nonlinear system in the chemical production process,and the traditional control method is difficult to meet the control accuracy requirements. In this paper,a fuzzy generalized predictive control method is proposed. The improved fuzzy partitioning clustering algorithm is used to identify the antecedent parameters of the Takagi-Sugeno(T-S) fuzzy model. The simulation result shows that the proposed algorithm is better than the original fuzzy clustering algorithm. At the same time,the recursive least squares method with forgetting factor is used to identify the post-parameter parameters of the fuzzy model.The generalized predictive control algorithm and PID algorithm are used to verify the CSTR system,simulation results demonstrate the effectiveness of the proposed method.