摘要
提出了一种新的Ｓｕｇｅｎｏ模糊模型辨识算法和对非线性系统进行并行化设计的方法．在Ｓｕｇｅｎｏ模糊模型辨识中，应用模糊聚类方法可将其前提结构和结论参数的辨识分开进行，减少了计算量；对于非线性系统的控制，Ｓｕｇｅｎｏ模糊模型实际上是动态系统的局部线性化，可采用并行设计的方法设计控制器，然后通过模糊推理得到全局控制量．最后通过倒立摆系统的控制说明了本文算法的有效性．
A new identification method of Sugeno's fuzzy model and parallel design for nonlinear system control are presented in this paper. For Sugeno's system identification, it is possible to separate the premise identification from the consequential identification using fuzzy cluster to simplify the calculation. In fact, the Sugeno's fuzzy model is a local linear model of the dynamical nonlinear control system, A parallel design method is proposed, and the total control law can be obtained by fuzzy inference. An inverted pendulum system control example is given to show the effectiveness.
出处
《自动化学报》
EI
CSCD
北大核心
1999年第4期488-492,共5页
Acta Automatica Sinica
基金
河北省自然科学基金
关键词
模糊控制
SUGENO模糊模型
系统辨识
参数辨识
Fuzzy control, Sugeno's fuzzy model, system identification, nonlinear system control.
