PSO-Tuned PID controller of a gantry crane system

Abstract

This project presents development of an optimal PID controller for controlling the nonlinear gantry crane system. The tuning method of Particle Swarm Optimization (PSO) with priority based fitness and linear weight summation approaches are implemented for finding optimal PID parameters. The effectiveness of both method are observed in order to find the optimal performances of system. The system dynamic model is derived using Lagrange equation. A combination of PID and PD controllers is utilized for positioning and oscillation control of the system. System responses including trolley displacement and payload oscillation are observed and analyzed. Simulation is conducted within Matlab environment to verify the performance of the controller. It is demonstrated that implementation of PSO is effective to move the trolley as fast as possible to the desired position with low payload oscillation.