Adaptive Control Algorithm Based on Linear Fuzzy Internal Models

Abstract

针对非线性对象,提出一种线性化模糊内模自适应控制算法。该算法以一组模糊规则作为非线性对象内部模型,一条模糊规则表示一个局部线性系统;根据对象输入与输出测量值,利用TSK建模方法在线辨识局部模糊内部模型;同时依据辨识模型设计局部H2最优模糊控制规则,所有规则构成H2最优模糊控制器。仿真实验显示:该算法适用于非线性对象的控制,具有较好的鲁棒性和抗干扰能力。A control algorithm which aimed at nonlinear plant is proposed. The control scheme adopts a group of fuzzy rule sets as internal model of the nonlinear plant, where a fuzzy rule set represents a local linear system. This algorithm utilizes TSK modeling scheme to identify fuzzy internal model on line by using the input and output measurement of the plant; at the same time it designs local fuzzy control rule set of linear quadratic optimal ( H 2 ) based on the identified model and all fuzzy control sets consist of H 2 fuzzy controller. It is shown in the simulations that the proposed control method is suitable for nonlinear plant and possesses satisfactory robust performance and disturbance rejection ability

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