基于T-S模糊模型的混沌系统鲁棒控制器设计

研究具有参数不确定混沌系统基于T S(Takagi Sugeno)模糊模型的鲁棒控制器设计。首先利用IF THEN模糊规则把不确定非线性系统的状态空间分成不同的区域,构建具有参数不确定性的T S模糊模型;然后提出使得系统在平衡点渐近稳定的鲁棒模糊控制器设计。该方法通过解一组线性矩阵不等式分别设计局部控制器,通过并行分布补偿的方法设计T S模糊系统的鲁棒控制器,渐近稳定性的条件更为宽松,能够有效降低鲁棒控制器设计的保守性。最后以Lorenz混沌系统为例,研究混沌系统的鲁棒控制器设计,仿真研究结果表明所设计的鲁棒控制器对参数不确定Lorenz混沌系统具有良好的控制效果。

Robust control of chaotic system based on T-S fuzzy model

A novel robust controller design of chaotic system with parametric uncertainties is proposed based on T-S (Takagi-Sugeno) fuzzy model. Firstly, through the partitions of the state space of uncertain nonlinear system into different regions by fuzzy IF-THEN rules, T-S fuzzy model with parametric uncertainties is constructed. Secondly, a robust controller is established, which guarantees that T-S fuzzy model is asymptotically stable near the system's equilibrium. By solving a set of linear matrix inequalities (LMI), this approach obtains the local feedback gains. The parallelly distributed compensation scheme is used to design the robust controller for the T-S fuzzy system. The condition of asymptotical stability is more flexible, and the conservativeness of robust fuzzy controller design is reduced. Finally, with Lorenz chaotic system, simulation results demonstrate the effectiveness of the proposed robust fuzzy controller.