基于简化Takagi-Sugeno模糊模型的系统镇定策略

Stabilizing strategy of system based on the simplified Takagi-Sugeno fuzzy model

针对Takagi-Sugeno型模糊控制器设计方法计算复杂且难以求解的问题,在分析原因的基础上,利用模糊规则将系统的输入输出空间划分为一个完备的模糊模式集,通过寻找与实时输入对应的模糊模式,对整个系统进行了简化。将该模型简化算法应用于一类非线性系统镇定问题的求解,利用Lya-punov稳定性分析理论和线性矩阵不等式等工具推导了闭环系统的可镇定条件,进而设计了相应的简化Takagi-Sugeno型模糊状态反馈控制器。仿真结果表明了这种模型简化方法的有效性。

Aiming at the problem that TakagiSugeno fuzzy controller is difficult to find the ordinary solutions and the computation is complex, the system′s input/output space is divided into a complete fuzzy pattern set by use of fuzzy rules. The overall system is simplified through searching the dominant fuzzy pattern related to the realtime input variables set. The stabilization problem of a class of nonlinear systems is studied based on the above model simplified algorithm. The conditions of stabilizing closedsystem are derived and the stabilizing fuzzy state feedback controller is designed through Lyapunov stability theory and linear matrix inequality respectively. The results of simulation show the effectiveness of the presented methods.