基于自适应差分进化算法优化的主动悬架单神经元PID控制  

Single neuron PID control of active suspension based on an optimized adaptive differential evolution algorithm

作　　者：焦蕊 赵强[1] 谢春丽[1] 李哲煜 JIAO Rui;ZHAO Qiang;XIE Chunli;RI Choiuk(School of Traffic and Transportation,Northeast Forestry University,Harbin 150040,China)

机构地区：[1]东北林业大学交通学院,哈尔滨150040

出　　处：《重庆理工大学学报（自然科学）》2022年第11期51-59,共9页Journal of Chongqing University of Technology：Natural Science

基　　金：黑龙江省自然科学基金项目(LH2021F002)。

摘　　要：为保证乘客乘坐舒适性和悬架控制效果达到最优,提出一种采用自适应差分进化算法优化的单神经元PID控制的主动悬架控制方法。建立了主动悬架的运动微分方程和状态空间模型,进一步设计了其单神经元PID控制模型,可以有效减少车身垂直加速度带来的影响。考虑到增益K和学习速率的参数值需要人为设定且多次试取难以确定最优参数,故采用自适应差分进化算法进行优化,以簧上质量加速度均方根值为目标函数,完成了主动悬架控制优化算法,并在Matlab/Simulink软件中进行仿真,对比被动悬架和分别由PID控制、单神经元PID控制和基于自适应差分进化算法优化单神经元PID控制的车身垂直加速度指标响应。仿真结果表明:采用自适应差分进化算法优化单神经元PID控制后,车身垂直加速度明显降低,控制效果更好,大幅提升了乘坐舒适性。In order to ensure the optimal passenger comfort and suspension control effect,this paper proposes an active suspension control method for PID-controlled single neurons,which is based on an optimized adaptive differential evolution algorithm.Firstly,the motion differential equation and the state space model of the active suspension are established,and its PID-controlled single neuron model is further designed,which can effectively reduce the influence of the vehicle vertical acceleration.Taking into account that the parameter values of the gain K and the learning rate need to be set manually,and it is difficult to determine the optimal parameters even by many trials,the adaptive differential evolution algorithm is then used to optimize the above four parameters,and the root-mean-square value of the sprung mass acceleration is used as the objective function to complete the optimization process.It is also simulated in Matlab/Simulink software to compare the passive suspension with vehicle vertical acceleration parameter response,the latter being respectively controlled by PID,single neuro PID and single neuron PID based on an optimized adaptive differential evolution algorithm.The simulation results show that,after using the adaptive differential evolution algorithm to optimize the PID-controlled single neurons,vehicle vertical acceleration is significantly reduced,the control effect is better,and the passenger comfort is greatly improved.

关 键 词：主动悬架 单神经元PID控制 差分进化算法 

分 类 号：U461[机械工程—车辆工程]