混沌系统的变论域模糊控制算法研究

混沌运动和混沌控制受到广泛关注,本文利用模糊控制实现混沌系统的控制.针对模糊控制器精度不高,模糊控制中规则数量与控制精度之间的矛盾,提出了一种基于蚁群优化算法的变论域模糊控制器.通过分析变论域模糊控制中的2类伸缩因子,指出其中1类并不能满足广义伸缩因子条件.提出利用蚁群优化算法对伸缩因子智能寻优的方法,在对蚁群算法改进的基础上,构成一种基于蚁群算法的变论域模糊控制,将设计的控制器用于Duffing混沌系统的控制.仿真结果表明,提出的控制算法在收敛速度和稳态性能上要略优于其他控制方式. 关键词： 混沌 变论域模糊控制 伸缩因子 蚁群优化算法

Research on the variable universe fuzzy algorithm of chaotic systems

Chaos and chaos control received extensive attention. The fuzzy controller is used to control chaotic systems in this paper. The accuracy of fuzzy controller is not high and there is contradiction between the number of control rules and accuracy. Accordingly a variable universe fuzzy controller based on ant colony optimization algorithm is proposed. By analyzing the two kinds of contraction-expansion factors, one of them was found unable to satisfy the general contraction-expansion factor condition. A method for optimizing the contraction-expansion factors intelligently via ant colony optimization algorithm is proposed. A variable universe fuzzy controller based on ant colony optimization algorithm is constituted and used to control the Duffing chaotic system. Simulation results show that the control method is superior to the others both in convergence speed and steady-state performance.