Abstract: Aiming at the problem that the selection of weight coefficient parameters in the linear quadratic regulator (LQR) control method of the air semi-active suspension system has limitations and relies to a large extent on manual experience. Taking advantage of the excellent global optimization search ability and parallel ability of the improved genetic algorithm, a strategy for optimizing the control parameters of LQR by the improved genetic algorithm (GA) is proposed. Firstly, establish the mathematical model of the quarter-vehicle semi-active suspension system, and build the simulation model with the LQR controller in the Simulink environment. Then, the simulation experiment of optimizing the LQR controller with the improved genetic algorithm is carried out. The simulation results show that, compared with the passive suspension system, under the random road conditions of Class B and Class C, the LQR controller based on the improved genetic algorithm reduces the peak of vehicle body acceleration by 42.17% and 47.23% respectively, improving the ride comfort of the vehicle.

Key words: semi-active suspension; LQR control; vehicle body acceleration; improved genetic algorithm

摘要： 针对空气半主动悬架系统线性二次型调节器（LQR）控制方法中权重系数参数选取存 在局限性，并在很大程度依靠人工经验的问题，利用改进遗传算法优秀的全局优化搜索能力 和并行能力，提出了一种改进遗传算法（GA）优化 LQR 控制参数的策略。首先，建立 1/4 车辆半主动悬架系统数学模型，并在 Simulink 环境下搭建带有 LQR 控制器的仿真模型；然后， 进行改进遗传算法优化 LQR 控制器的仿真实验。仿真结果显示，与被动悬架系统相比，在 B、 C 级随机路面条件下，基于改进遗传算法的 LQR 控制器使得车身加速度峰值分别下降了 42.17%、47.23%，提高了车辆的乘坐舒适性。

关键词: 半主动悬架；LQR 控制；车身加速度；改进遗传算法