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Performance Analysis for a Gantry Crane System (GCS) using Priority-based Fitness Scheme in Binary Particle Swarm Optimization

机译:使用基于优先级的群群优化中的优先级的健身方案的龙门起重机系统(GCS)的性能分析

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This paper presents development of an optimal PID and PD controllers for controlling the nonlinear Gantry Crane System (GCS). A new method of Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is developed to obtain optimal PID and PD parameters. The optimal parameters are tested on the control structure to examine system responses including trolley displacement and payload oscillation. The dynamic model of GCS is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of the system in terms of settling time, steady state error and overshoot. The result not only confirmed the successes of using new method for GCS, but also shows the new method performs more efficiently compared to the continuous PSO. This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the desired position with low payload oscillation.
机译:本文介绍了用于控制非线性龙门起重机系统(GCS)的最佳PID和PD控制器的开发。开发了一种使用基于优先级的健身方案的二进制粒子群优化(BPSO)算法的新方法来获得最佳PID和PD参数。在控制结构上测试最佳参数,以检查包括Trolley位移和有效载荷振荡的系统响应。使用拉格朗日方程导出GCS的动态模型。模拟在Matlab环境中进行,以验证系统的性能,以稳定时间,稳态误差和过冲。结果不仅确认了使用GCS的新方法的成功,而且还显示了与连续PSO相比更有效地执行新方法。该提出的技术表明,BPSO中基于优先级的健身方案的实施是有效的,并且能够尽可能快地将推车迅速移动到具有低有效载荷振荡的所需位置。

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