Optimal RTGC Controller using Robust PID H∞ Integral-Backstepping under Payload Mass and Rope Length Uncertainties

The increase in goods traffic between countries and islands requires the availability of port automation so that the distribution of goods is faster and the quality is guaranteed. One of the control problems for automating the port is controlling the position and sway angle of the container on the Rubber Tyred Gantry Crane (RTGC). However, the RTGC system's model is often uncertain because of the uncertainty in the mass of the payload and the length of the hauling rope when operating. This paper proposes a robust PID controller based on
$H$

∞
integral backstepping to overcome this problem. Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic Algorithms (GA) are used to optimize the parameter of
$H$
∞
integral backstepping so that the system response follows the desired trajectory. The results show that the control system designed can provide a satisfactory solution to variations in the mass and length of the rope. PSO and SA give better optimal and robust performance than GA.