基于遗传算法优化的汽车半主动悬架PID控制仿真研究

Simulation research of the PID controller of vehicle suspension based on the genetic algorithm

PID控制器在汽车半主动悬架应用中存在参数确定的问题,针对这一问题设计了一种基于遗传算法优化整定PID参数的方法。该方法利用遗传算法的全局优化能力,以半主动悬架的性能指标为目标函数对PID参数进行优化设计。应用该方法进行汽车半主动悬架平顺性仿真。仿真结果表明,基于遗传算法优化的PID控制器的汽车半主动悬架相对于PID控制主动悬架以及被动悬架而言,改善了车身垂向加速度和悬架动行程。同时在充分利用PID控制器优势的基础上,改善了其参数确定过程中存在的问题。

Due to the shortcoming of the PID controller when defining the three parameters, a method using the genetic algorithm is designed to optimize such controller. This method utilizes the global optimization algorithm of the genetic algorithm to optimize and design the parameters with the target function of chassis performance indexes. And then a simulation experiment is provided for the active vehicle chassis control. The results show that the performances of the actively controlled vehicle chassis using the PID controller optimized by the genetic algorithm such as the vertical acceleration and the dynamic displacement of the suspension can be greatly improved, compared to the chassis controlled by the normal PID and the passive one. Meanwhile, the problem of de-fining the weight matrices is greatly solved based on the advantage of the normal PID controller is sufficiently utilized.