基于遗传算法的汽车主动悬架控制器优化设计  

Optimal Design of Active Suspension Controller Based on Genetic Algorithm

作　　者：桑楠[1] 白玉[1] 李玉芳[2] 

机构地区：[1]常州工学院,常州213002 [2]南京航空航天大学,南京210016

出　　处：《机械科学与技术》2013年第9期1400-1404,共5页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(51005113)资助

摘　　要：针对LQR方法设计主动悬架控制器存在的不足,研究遗传算法与LQR方法结合优化汽车主动悬架控制器的设计。建立汽车半车模型的动力学方程,应用随机线性最优控制理论设计车辆主动悬架LQR控制器,并在Matlab/Simulink环境中实现该控制器的数值仿真,根据仿真结果运用遗传算法对控制器性能参数进行优化。对优化控制器的仿真结果进行时域和频域分析,结果表明:遗传算法与LQR方法相结合,能较快收敛到最优解;优化的主动悬架控制器可以较好地改善车辆舒适性。In the lack of using LQR（ Linear Quadratic Regulator） method to design active suspension controller, a combined genetic algorithm and LQR optimal design method for automotive active suspension controller was studied. To establish the dynamics equations of the vehicle half-car model, LQR controller of active suspension is designed based on stochastic linear optimal control theory, and numerical simulation of the controller is carried out in Mat- lab/Simulink environment. According to the simulation results, the performance parameters of controller are opti- mized using genetic algorithm. Simulation results for controller optimization in time-domain and frequency domain shows that the combined genetic algorithm and LQR optimal design method can quickly obtain the optimal solution; optimized active suspension controller can be used to improve vehicle riding comfort.

关 键 词：主动悬架 控制器 遗传算法 优化 仿真 

分 类 号：U461[机械工程—车辆工程]