PSO-GA组合算法优化PID参数及可视化平台设计

PID Parameters of PSO-GA Combination Algorithm Optimization and Design of Visual Platform

PID控制是机床伺服控制系统中广泛应用的一种控制方式,PID参数是否合理直接影响着伺服系统的性能。以MKS8332A数控凸轮轴磨床砂轮架伺服系统为模型,提出一种基于粒子群-遗传组合算法(PSO-GA)的PID控制器参数优化方法。仿真结果表明,该算法寻优性能比单独的遗传算法和粒子群算法表现更为优异,证实了该算法能有效的优化伺服系统PID参数。为了使用户无需去了解复杂的算法源代码,而只需在平台上进行操作就可以解决PID参数的优化问题。多种智能算法被引入称为可视化平台的优化软件设计,用MATLAB GUI编程环境构建了PID参数可视化平台,为用户提供一个友好的图形界面。

PID control is widely used in machine tool servo control system.Whether the parameters are reasonable or not is very important to affect the performance of the servo control system.MKS8332A CNC camshaft grinding wheel servo system is seen as a model,PID controller parameters optimization method based on PSO-GA combination algorithm is proposed.The simulation results in PID controller parameters optimization show that the algorithm is superior to the single GA or PSO algorithm,which confirmed that the algorithm can effectively optimize the PID controller parameters of the servo system.In order not to make users need to understand the complex source code of the algorithms,optimization problem of PID parameters can be solved just to execute operations on the platform.Some intelligent algorithms are introduced to the optimization software,called visual platform,using MATLAB GUI programming environment to construct PID parameters visual platform,which provide a friendly graphical interface for users.