基于模糊集值统计的输出跟踪控制器设计

Output Tracking Controller Based on Fuzzy Set Data-Statistics

提出基于模糊集值统计下修改模糊推理模型的控制规则库方法。对于具有不确定因素的非线性系统,当外界条件和系统内部结构参数变化时,根据系统的输入输出数据对,首先建立控制规则库的估计函数,引入相似度概念,在线修改隶属函数,使实际输出跟踪期望值的变化。通过仿真验证表明,该方法对于非线性、不确定性复杂系统可以获得满意的跟踪控制效果。

An approach for correcting the controlling rule base of a fuzzy inferring model based on fuzzy set data-statistics is studied and the method can make the controller effectively track expectation values. An estimating formula for controlling the rule base is established to enable membership functions to be on-line amendment according to system input-output pares, as environment conditions and system inner structure parameters are changed. By introducing the concept of ＂similarity＂ the rule computation time and the rule volume are reduced. Through the mathematical simulation the approach is proved to be applica Key ble to design fuzzy controllers for non-linear systems with uncertainties.