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

Abstract

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.