Optimization of Gantry Crane PID Controller Based on PSO, SFS, and FPA

The problem of gantry crane automation has become increasingly important due to its wide application in ports and construction. Operating errors can cause various problems such as damage to goods, delays in operations, excess costs, and threaten the lives of workers. Therefore, automatic control needs to be applied to control the position and its sway angle. To obtain an accurate movement and minimal sway, optimization of the controller in gantry crane automation should be considered. This paper will introduce an alternative method of optimization techniques namely Stochastic Fractal Search (SFS) and Flower Pollination algorithm (FPA) for the PID controller, which is applied to control the position and sway angle of the gantry crane. For the comparison purposes, the control results will be compared with the PID controller optimized using PSO technique. For position control, SFS and FPA lead to better speed response and accuracy than compared to PSO. In terms of sway-cancellation PSO has a better settling time, but with the trade-off of longer settling time for angles, SFS and FPA are still able to provide better results because the sway angle settling time is below the position settling time.