Surge Speed and Yaw Angle Control System Design on Unmanned Surface Vehicle (USV) Using PID-Fuzzy-Genetic Algorithm

In today’s era of rapid technological and communication advancements, human tasks are increasingly supported by technology, including the development of Unmanned Surface Vehicles (USVs). This study centers on the design and implementation of control systems for USVs, focusing specifically on surge speed and yaw angle. The controller enhancement in this research involves optimizing the PID-Fuzzy controller from previous studies. The chosen optimization method is a genetic algorithm, which fine-tunes the membership functions of the PID-Fuzzy controller to achieve the lowest error values in managing surge speed and yaw angle. The FIS (Fuzzy Inference System) of the optimal generation then undergoes closed-loop testing on both control systems. The simulation results demonstrate that the PID-Fuzzy-GA significantly reduces the cross-track error (XTE) for the yaw heading angle to 62022, compared to 62199 and 62192 for the PID and PID-Fuzzy controllers, respectively. Additionally, the PID-Fuzzy-GA controller markedly decreases the error areas in surge speed. This method achieves the lowest error, reducing it by up to 7.1577%, and also minimizes %Overshoot while accelerating rise time. The optimal generation produced by the genetic algorithms allows USVs to follow the track more precisely compared to other controllers.