基于粒子群优化的主动悬架PID控制策略

针对汽车主动悬架比例-积分-微分控制器（proportional-integral-derivative,PID）参数选择问题，传统PID控制参数整定具有一定的盲目性。设计粒子群优化算法，目标函数根据悬架性能指标建立，利用粒子群优化算法，优化PID控制器中的参数。结果表明，与优化前PID控制的主动悬架相比，采用粒子群优化PID控制的汽车主动悬架的性能指标有了明显的提升。最终得出结论，经过粒子群算法（Particle swarm algorithm，PSO）优化后PID控制提升了汽车行驶平顺性及操纵稳定性，同时解决了PID控制器参数整定的问题。

PID control strategy of active suspension based on particle swarm optimization

In view of the proportional integration-derivative (PID) controller parameter selection problem of automotive active suspension, the traditional PID control parameter setting has certain blindness.The particle swarm optimization algorithm is designed. The objective function is established according to the suspension performance index. The parameters of PID controller are optimized by using particle swarm optimization algorithm.The results show that compared with the active suspension with PID control before optimization, the performance index of the vehicle active suspension with PSO optimization PID control has been significantly improved.Finally, it is concluded that PID control optimized by Particle swarm algorithm (PSO) improves vehicle ride comfort and handling stability, and solves the problem of PID controller parameter setting.