摘要
研究汽车悬架稳定性控制优化问题,由于PID控制器在汽车主动悬架中参数的选择决定汽车行驶的稳定性能。针对传统参数整定的方法存在盲目性,设计了一种用粒子群算法优化整定PID参数的方法。利用粒子群算法的并行全局搜索策略,以主动悬架性能指标为目标函数对PID参数进行优化设计。应用改进方法对汽车悬架主动控制系统进行仿真。仿真结果表明,用粒子群算法优化的PID控制器的汽车主动悬架相对于PID控制主动悬架及被动悬架而言,改善了车身垂向加速度和悬架动行程。同时解决了PID控制器参数整定的问题。
ABSTRACT： Due to the problem of the PID controller when defining the three parameters, a method using the PSO algorithm was designed to optimize it. This method utilizes the global searching strategy of the PSO algorithm to opti- mize and design the parameters with the target function of chassis performance indexes. And then a simulation experi- ment was provided for the active vehicle chassis control. The results show that using the PID controller optimized by the PSO algorithm, the actively controlled vehicle chassis＇s performances, such as the vertical acceleration and the dynamic displacement of the suspension, can be greatly improved compared with the chassis controlled by the normal PID controller and the passive one. Meanwhile, the problem of defining the weight matrices is wess solved based on the advantage that the normal PID controller is sufficiently utilized.
出处
《计算机仿真》
CSCD
北大核心
2013年第4期155-158,168,共5页
Computer Simulation
基金
江苏省自然科学基金项目(BK2011367)
江苏省"六大人才高峰"资助项目(SZ2010002)
关键词
悬架
粒子群算法
仿真
Suspension
PSO algorithm
Simulation
