间歇过程模糊预测学习控制器的设计与仿真

Design and Simulation of Fuzzy Predictive Learning Controller for Batch Process

针对工业间歇过程的控制问题,分析比较了现有的两类反馈-前馈迭代学习算法在解决工业间歇过程控制系统滞后问题上的缺陷,采用T-S模糊预测模型,在原有反馈-前馈迭代学习算法基础上引入预测思想,研究了基于模糊预测的迭代学习算法,并设计了一种模糊预测学习控制器。以具有滞后、变参数特性的间歇过程为例,进行了仿真研究,验证了提出方法的有效性。

As for the control of industrial batch processes, it is the limitation of the two existent kinds of feedback-feed forward iterative learning algorithm to solving delayed questions of industrial batch process control systems that is analyzed and compared. Based on these, T-S fuzzy predictive model was adopted. Predictive idea was introduced into the old feedback-feedforward iterative learning algorithm. An improved algorithm of iterative learning control （ILC） based on fuzzy prediction was researched and a kind of fuzzy predictive learning controller was designed. The batch process with the pure lag and time-variation parameters was simulated, which turned out that the method works well.