单值模糊广义预测控制及其在热工对象中的应用

Simplified general predictive control and its application in thermal system

热工火电机组具有非线性、时变性、大时滞等特性,工业控制中有一定的难度。在前人对T-S模型辩识研究的基础上,本文提出了一种自适应模糊模型辨识算法,通过置信度检验,自适应改变模糊规则数,确保保留最有效的模糊规则。在此基础上,本文提出了一种基于T-S模型的单值模糊广义预测控制策略,与基本模糊广义预测控制算法相比较,该算法具有结构简单、计算过程快的优点。仿真结果表明,该算法明显地改善了控制系统的控制品质。

Because of the characteristics, such as non-linearity, time-variant parameters and long time-delay, it is very difficult to control the thermal power unit. Based on the presented research about T-S model identification algorithm, an adaptive simplified fuzzy-model identification algorithm is proposed in this paper, which can change the number of fuzzy rules adaptively to ensure that the most effective fuzz rules are remained through testing the belief degree. Furthermore, a general predictive control algorithm based on T-S model is proposed in this paper. Compared with basic fuzzy general predictive control algorithm, this new algorithm features simple structure and fast calculation. Simulation results show that this new control algorithm can improve the performance of the control system effectively.