摘要
为了解决模糊系统建立过程中规则数目的选择问题,提出了一种模糊系统建立方法。该方法利用K均值法计算聚类中心,不需要预先给出聚类的数目,聚类的数目根据聚类准则函数的收敛性决定,同时在算法结构中引入补偿因子以增强算法的稳定性,再结合梯度下降法辨识后件参数,从而得到模糊系统。与传统的模糊系统建立方法进行比较,该方法提高了辨识精度且能自动生成模糊规则,避免了规则数目选取的盲目性。最后将该方法用于辨识单元机组的协调控制系统,仿真结果表明了该算法的有效性和快速性。
To solve the problem that how to select the rule number in the establishment of fuzzy system, a new establishment method is suggested. The cluster center is calculated using K-means algorithm. The number of clusters is determined by the convergence of cluster principle function. A compensation factor is introduced to improve the stability. algorithm is used to identify parameter of consequent part of rule base. This method coordinated control system of power unit.Simulation results prove the validity of this method.
出处
《华北电力大学学报（自然科学版）》
CAS
北大核心
2006年第4期16-19,共4页
Journal of North China Electric Power University：Natural Science Edition
关键词
辨识
聚类
补偿
模糊系统
identification
cluster
compensation
fuzzy system
