一种基于T-S模型的模糊预测控制

提出了一种基于T-S模型的模糊预测控制策略。T-S模糊模型用来描述对象的非线性动态特性,通过当前的工况参数实时在线的修正每一时刻的阶跃响应模型参数,将模糊模型作为常规线性预测控制DMC方法的预测模型,从而把T-S模型对复杂的非线性系统的良好描述特性和预测控制的滚动优化算法相结合,来实现利用常规线性预测控制策略对非线性系统的有效控制,有效地解决了复杂工业过程的强非线性问题。pH中和过程的仿真结果表明其性能明显优于传统的PID控制器。

A Fuzzy Predictive Control Based on T-S Model

This paper proposes an approach to Fuzzy Predictive Control based on a fuzzy model of the Takagi- Sugeno form. T- S fuzzy model is used to approximate the dynamics of nonlinear processes. In our approach, step responses for different operating points are extracted on- line from the fuzzy model and a modified linear DMC algorithm is used. In this way, all the advantages of both fuzzy modeling of nonlinear processes and DMC control are accomplished. It makes use of the conventional linear Model Predictive Control strategy to complete the valid control of the nonlinear system, and resolves the strongly nonlinear problem of complicate industrial process availably. Simulation result on a pH neutralization process demonstrates its control performance is superior to conventional PID controller.