基于模糊控制律的遗传神经匝道协调控制

讨论了快速路匝道系统中智能控制技术问题。针对匝道系统特点,分析了模糊控制、人工神经网络、遗传算法的适用性,提出了一种基于模糊控制律的遗传神经匝道协调控制方案。在该方案中,对模糊控制输入输出数据进行线性修正,使用修正后的数据完成遗传神经网络训练,并用神经网络代替模糊控制器对匝道系统进行控制。给出了神经网络结构和遗传算法流程,并结合宏观交通流模型进行系统仿真。仿真结果表明,与模糊控制相比,控制效果显著提高。

Coordinated Ramp Metering Based on Fuzzy Control Law and Genetic-Neural Algorithm

The application of intelligent control technology to the ramp system of urban freeway is discussed.Based on the adaptability analysis of fuzzy control,neural networks,and genetic algorithm to the ramp system,a coordinated ramp metering combining both fuzzy control law and genetic-neural algorithm is proposed.The inputs and outputs of fuzzy controller are linearly updated and are used for the training of genetic-neural networks.The trained neural networks are then used in the ramp system to replace fuzzy controller.The structure of the neural networks and genetic algorithm process are also presented.With a macroscopic traffic flow model,the simulation results show that,in comparison with conventional fuzzy control law,the proposed method can improve the system performance significantly.