基于ANN的专家自调整模糊控制器的设计

Self-tuning Fuzzy Expert Controller and Its Application

针对工业中被控对象的非线性、滞后和时变特性,采用常规模糊控制系统可能存在难于形成特定约束下的规则集以及确定其比例因子、量化因子比较复杂的问题,使用混合智能控制策略和基于ANN设计了专家控制器,借助于专家经验可以自调整模糊控制器的量化因子和比例因子并实现控制规则集。仿真结果表明了该控制器的有效性。

Specifically for controlled member nonlinearity , lagging and time are changed into characteristic property in industry, the it＇s proportion factor forming the regulation collection under specially appointed constraint and ascertaining that , quantization factor difficult to adopt routine to mix up navar are comparatively complicated. To design the expert controller based on the nerve network. To intelligence control through adjustment of the quantification factor and the proportionality factor of the fuzzy controller. The simulation results prove this controller is effective.