遗传算法在受电弓主动控制器中的应用

为了提高高速列车的受流能力,降低离网率,本文以线性二次型最优控制为基础设计了受电弓的主动控制器.针对线性二次型最优控制中权矩阵Q和R的取值问题,采用遗传算法进行优化,通过系统的动态性能指标计算出系统的目标函数并得到权矩阵的最优值,解决了传统线性二次型最优控制中权矩阵由经验设计所带来的全局最优难实现的问题.通过仿真分析不同时速下接触网的刚度变化和弓网之间接触压力的参数变化,本文设计的主动控制器能够很好的减小和控制接触压力的波动,提高了弓网系统的动态性能指标.

Application of Genetic Algorithm in Active Controller of Pantograph

In order to improve the current collection ability of high-speed train and reduce the off-grid rate, this study designs the active controller of pantograph based on linear quadratic optimal control. Aiming at the problem of weight matrix Q and R in the linear quadratic optimal control, genetic algorithm is used to optimize. The objective function of the system is calculated by the dynamic performance index of the system and the optimal value of the weight matrix is obtained. And it solves the problem that the weight matrix is difficult to realize the global optimal in traditional linear quadratic optimal control by the experience design. Through the simulation and analysis of the change of catenary stiffness and the change of contact pressure parameters between pantograph and catenary at different speeds, the active controller designed in this study can reduce and control the fluctuation of contact pressure, and improve the dynamic performance index of pantograph and catenary system.