The PID prediction control system using particle swarm optimization and genetic algorithms

GuoDong Li, Chen-Hong Wang, S. Masuda, D. Yamaguchi, M. Nagai
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引用次数: 3

Abstract

In this paper, the particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are employed to optimize the parameters of PID algorithm in order to improve the performance of PID control system. Moreover, we propose the grey model based on grey system theory to combine with PID control to establish the PID prediction control system. The proposed control system can realize the accurate control in realtime. Finally, we validated the effectiveness of the proposed control system by computer simulation.
PID预测控制系统采用粒子群优化和遗传算法
本文采用粒子群优化(PSO)算法和遗传算法(GA)对PID算法的参数进行优化,以提高PID控制系统的性能。在此基础上,提出了基于灰色系统理论的灰色模型与PID控制相结合,建立了PID预测控制系统。所提出的控制系统可以实现精确的实时控制。最后,通过计算机仿真验证了所提控制系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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