基于遗传算法高速公路混沌系统模糊延迟反馈匝道控制

On-ramp chaos control of freeway system with fuzzy delay feedback based on genetic algorithm

研究采用延迟反馈法和模糊控制相结合的高速公路混沌匝道控制问题。针对高速公路非线性与不确定性特点,提出延迟反馈和TS模糊控制相结合的高速公路混沌控制方法,简介具有开关功能的高速公路匝道混沌控制原理,通过交通流混沌在线智能识别子系统实时计算最大李雅普诺夫指数,识别系统是否处于混沌状态,作为加入混沌控制信号的条件;设计将高速公路不稳定周期运动转化为周期运动作为控制目标,系统状态变量的延迟信号与其本身信号的差值和误差变化作为控制器输入,匝道调节率作为控制变量的模糊混沌控制器;在专家经验的基础上,采用遗传算法对控制器参数进行优化学习;仿真试验分析该控制方法的控制效果,证明该原理与方法的可行性与正确性。

Chaos control in freeway system is studied by using a fuzzy delayed feedback control method. Based on the nonlinear and uncertain characteristics of freeway chaos system, a synthetic method is proposed to control the freeway chaos by using the theory of delay feedback control and the Takagi-Sugeno（TS） fuzzy control method. The principle on the switching system of on-ramp chaos control in freeway is briefly introduced. The chaos control signal will be used as the input, if the maximal Lyapunov exponent is positive, by using the intelligent real-time recognition method for chaos in traffic flow. The feedback ramp controller is designed. The goal of chaos control is to realize periodic orbits from unstable periodic movements. The error and its variation between the signal of the system state variables and its delayed signals are the input variables for the chaos controller. The ramp metering rate is the output variable. Based on the experiences of the experts, the parameters of the TS fuzzy controller are optimized by using genetic algorithm. The effects are discussed in the stimulation experiment. The results indicate that both the principle and the method are correct and feasible.