一类耦合映射模糊时滞跟驰系统的反馈控制

Feedback Control of a Class of Coupled-Map Fuzzy Time-Delay Car-Following System

由于驾驶员在感应车间距变化时存在时变滞后的问题,且其灵敏度随着不同的车速和车间距在一定范围内波动,为了准确描述车辆在行驶过程中的运行状态,文中在耦合映射(CM)跟驰模型基础上,提出了一类模糊滞后CM跟驰模型,并对该模型的稳定性进行了分析.利用Lyapunov函数给出了模糊控制器存在的充分条件,使闭环跟驰系统满足稳定性,即交通拥挤现象能够得到有效抑制,并通过求解线性矩阵不等式(LMI)得到所设计的控制器.仿真实验表明,在该模糊控制器作用下,各辆车的速度震荡幅度得到了有效的降低,且能够更快地恢复到平稳状态,同时有效降低了车辆的二氧化碳排放量,说明该方法对于抑制交通拥挤和降低二氧化碳排放量是有效的.

When a driver is sensing headway, there exists a time-varying delay, and the sensitivity of the driver changes with the speed and the headway within a certain range. In order to accurately describe the running state of vehicles, on the basis of coupled-map car-following model, a new coupled-map fuzzy car-following model with time- delays is proposed, and the stability of the new car-following model is investigated. Then, by using Lyapunov func-tion, the sufficient condition of the existence of a fuzzy controller is given. Under this condition, the closed-loop system achieves an asymptotic stability, that is, traffic congestion phenomena can be effectively suppressed. Finally, the fuzzy controller is obtained by solving a linear matrix inequality （ LMI） . Simulation results show that, with the help of the fuzzy controller, the car achieves smaller amplitude of velocity oscillation, faster process of recovering to an equilibrium state, and lower emission of carbon dioxide, which means that this method is effective in suppressing traffic congestion and reducing carbon dioxide emissions.