基于广义T-S模糊辨识模型的混沌系统模糊控制
doi: 10.3724/SP.J.1146.2006.00050
Identifying Chaotic System Based on Adaptable T-S Fuzzy Model and Algorithms of GA-Annealing Strategy
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摘要: 该文针对混沌系统辨识引入广义T-S模糊模型，并对T-S模糊模型自适应参数进行遗传退火算法优化，使系统具有最佳结构和参数。在此基础上给出了广义T-S模糊模型使系统渐近稳定模糊控制算法，并证明了广义T-S模型有足够的精度, 控制的精度就能得到满足，系统可以跟踪目标。控制的目标可以为周期轨道,也可以为连续变化的目标函数。以一维的Logistic 系统和二维的Henon系统为例进行仿真分析，结果表明该方法的有效性和可行性。Abstract: A adaptable T-S fuzzy model which membership functions , structure and parameters optimized by the algorithms of GA-Annealing strategy is proposed to identify chaotic system . Based on this, the asymptotic stability algorithm of fuzzy control having simple and effective control laws is employed. That the system can efficiently track the objective functions which can be either period orbits or continuous variable functions is also proved , if the precision of the adaptable T-S fuzzy model is good. The simulations to control chaotic system models of Logistic system and Henon system show the effectiveness and feasibility of the proposed method.
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