基于遗传算法的车辆4自由度主动悬架最优控制研究

Optimal control of vehicle active suspension with four degrees of freedom based on genetic algorithm

文章首先建立车辆4自由度主动悬架系统模型,然后针对悬架系统的控制问题,基于结合遗传算法和最优控制理论,提出悬架系统的最优控制策略。该控制方法利用遗传算法对LQR控制器的加权矩阵Q和R参数进行自适应调整优化,不仅可以避免传统的主动悬架LQR最优控制器设计中存在人为主观因素的问题,还能实现悬架系统的自适应最优控制。仿真实验结果表明,在不同车速和路面等级的行驶工况条件下,相比于传统的LQR控制方法,基于遗传算法优化的LQR控制能提高主动悬架系统的控制性能,使车辆获得更优的乘坐舒适性和操纵稳定性,研究结果为探寻有效的主动悬架控制策略、改善车辆的行驶性能提供了有用的控制方法参考。

In this paper ,a dynamical model of vehicle active suspension with four degrees of freedom is built ,and based on genetic algorithm and optimal control theory ,a linear‐quadratic regulator （LQR） control strategy for controlling active suspension is presented .In this scheme ,the genetic algorithm is used to realize the optimal search for the weighted matrix Q and the weighted parameter R of the LQR controller .This method not only overcomes the subjective factors in the design course of the tradition‐al LQR controller but also can realize the adaptive optimal control of suspension system .The simula‐tion results demonstrate that under the driving cycles with various grade roads and vehicle speed ,the presented LQR control method can obtain better control performance than the traditional one ,and can further improve ride comfort and handling stability of vehicle .The research results can provide useful theoretic reference for exploring the control methods of vehicle suspension system and improving the driving performance of the vehicle .