高速列车半主动悬挂系统遗传优化模糊控制

为有效抑制高速列车车体的横向振动，在ADAMS/Rail软件中建立列车横向半主动悬挂动力学模型，在Matlab中编写遗传算法程序，提出采用浮点数与整数混合编码和基于个体适应度值标准差的自适应遗传交叉、变异概率的方法，优化半主动模糊控制器的量化因子、比例因子、隶属度函数和模糊规则，以车体前后两端横向振动加速度的均方根值作为遗传算法优化性能指标，不断优化半主动悬挂系统的模糊控制器。联合仿真结果表明：采用遗传优化设计模糊半主动悬挂，能有效抑制车体横向振动加速度，改善列车的乘坐舒适性。

GA-optimized Fuzzy Control of Semi-active Suspension System for High-speed Train

In order to reduce lateral vibration of high-speed strain, the dynamics model for semi-active suspensions of vehicles was established in ADAMS/Rail code. Programs for genetic algorithm procedures were written in MATLAB code using a mixed encoding method of float and decimal numbers, and the method of adaptive genetic crossover and mutation probability based on standard deviation of fitness values. The membership functions, fuzzy rules, quantification factors and scaling factors were optimized. Using the RMS of lateral vibration at the front and the rear of the vehicle’s body as the performance index of the genetic algorithm, the fuzzy controller of the semi-active suspension was constantly optimized. The joint simulation results show that using GA-optimized fuzzy semi-active suspension can effectively reduce the lateral vibrations and improve the ride comfort of vehicles.