基于HPSO的PID算法在汽油机怠速控制中的应用

Application of HPS Optimization Based PID Algorithm to Idle Speed Control of Gasoline Engine

在怠速控制系统中,PID控制器的参数整定直接影响到控制效果;介于标准粒子群算法的不足,采用混合粒子群算法对PID控制器的参数进行离线整定,并基于MATLAB软件进行仿真实验;实验结果表明:混合粒子群的寻优精度优于遗传算法和标准粒子群算法,且具有良好的收敛速度。

In idle speed control system, the setting of PID controller parameters directly affects the effect of the control. According to the shortcomings of standard particle swarm algorithm, hybrid particle swarm optimization （HPSO） algorithm is used to make offline setting for the parameters of PID controller, simulation experiment is conducted based on MATLAB software, and experiment results show that the searching accuracy of hybrid particle swarm algorithm is better than that of genetic algorithm and standard particle swarm algorithm and has good convergence speed.