Optimal PID controller tuning of automatic gantry crane using PSO algorithm

M. I. Solihin, Wahyudi, M. Kamal, A. Legowo
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引用次数: 48

Abstract

In this paper, a novel method for tuning PID controller of automatic gantry crane control using particle swarm optimization (PSO) is proposed. PSO is one of the most recent optimization techniques based on evolutionary algorithm. PSO is also known as computationally efficient method. This work presents in detail how to apply PSO method in finding the optimal PID gains of gantry crane system in the fashion of min-max optimization. The simulation results show that with proper tuning a satisfactory PID control performance can be achieved to drive nonlinear plant. The controller is able to effectively move the trolley of the crane in short time while canceling the swing angle of the payload hanging on the trolley at the end position. The robustness of the controller is also tested.
基于粒子群算法的自动龙门起重机PID控制器最优整定
提出了一种利用粒子群算法对自动龙门起重机PID控制器进行整定的方法。粒子群优化是一种基于进化算法的最新优化技术。粒子群算法也被称为计算效率高的方法。本文详细介绍了如何应用粒子群算法以最小-最大优化的方式寻找龙门起重机系统的最优PID增益。仿真结果表明,通过适当的整定可以获得满意的PID控制性能来驱动非线性对象。该控制器能够在短时间内有效地移动起重机小车,同时消除小车末端位置悬挂载荷的摆动角度。最后对控制器的鲁棒性进行了测试。
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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