基于粒子群算法的直流电机PID控制器改进设计

A. El-Gammal, A. A. El-Samahy
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引用次数: 60

摘要

本文提出了一种新的粒子群优化技术,用于自适应调节PID速度控制器的增益,以使单独励磁直流驱动器的速度需求与输出响应之间的积分绝对误差最小,稳定时间最小,超调最小。新技术通过使用指定或选择的加权因子导出单个聚合目标函数,将所有目标函数转换为单个目标函数。由于最优PID控制器参数依赖于所选择的权重因子,因此在粒子群优化中,权重因子也被视为动态优化参数,即PID控制器最优参数和最佳权重因子集的双重优化和全局选择。计算机仿真和实验结果表明,最优PID控制器的性能优于传统PID控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified design of PID controller for DC motor drives using Particle Swarm Optimization PSO
This paper presents the application of a new Particle swarm optimization technique for adjusting the gains of a PID speed controller adaptively to give the minimum integral absolute error between the speed demand and the output response, minimum settling time, and minimum overshoot for a separately excited dc drive. The new technique converts all objective functions to a single objective function by deriving a single aggregate objective function using specified or selected weighting factors. Since the optimal PID controller parameters are dependent on the selected weighting factors, the weighting factors was also treated as dynamic optimizing parameters within the Particle Swarm Optimization as a dual optimization and global selection of PID controller optimal parameters as well as best set of weighting factors. Computer simulations and experimental results show that the performance of the optimal PID controller is better than that of the traditional PID controller.
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