A Development of Fuzzy-PID Controller Applied on an Autonomous Surface Vehicle

Abstract

Precise trajectory tracking remains a significant challenge for Autonomous Surface Vehicles (ASVs) due to their inherent nonlinear and strongly coupled surge-sway-yaw dynamics, which are often exacerbated by environmental disturbances. This study aims to enhance the trajectory tracking performance and robustness of an ASV by developing an adaptive Fuzzy-PID controller and comparing its efficacy against a conventional Proportional-Integral-Derivative (PID) controller. A comprehensive 3 degree of freedom (DoF) mathematical model of the ASV is derived using the Fossen modeling framework, incorporating rigid-body kinetics, hydrodynamics, and environmental disturbances. A novel single-loop Fuzzy-PID control architecture is then proposed, wherein a Mamdani-type fuzzy inference system dynamically tunes the PID gains online based on the tracking error and its derivative. The performance of the proposed controller is rigorously evaluated against a classical PID controller through simulations involving circular and figure-eight trajectories, which are designed to stress the system's dynamic coupling. The simulation results demonstrate the superior performance of the Fuzzy-PID controller. It achieves a substantial reduction in steady-state heading bias up to 46% in Root Mean Square Error (RMSE) and 64% in Integral Absolute Error (IAE) for the circular trajectory compared to the conventional PID. Furthermore, the proposed controller delivers smoother control signals, faster settling times, and improved robustness under strong dynamic coupling and external perturbations. The proposed Fuzzy-PID controller provides a significant improvement in tracking accuracy and adaptability over the conventional PID controller. It offers an efficient and practical solution for the autonomous guidance and control of small-scale surface vehicles, effectively handling nonlinearities and coupled dynamics. Future work will focus on hardware-in-the-loop validation and incorporation of advanced disturbance observers.