Under-ice Trajectory Tracking for Underwater Gliders Using Fuzzy-based Adaptive Control

Our study introduces a dual-layer fuzzy-based adaptive control framework tailored for underwater gliders (UGs) navigating beneath ice-covered waters. This system, crafted employing the backstepping technique, is validated for stability through Lyapunov functions. Incorporating a fuzzy linear adaptation law enhances the capacity to estimate unknown bounded environmental disturbances. Furthermore, we streamline the tuning of controllers through the application of particle swarm optimization (PSO) methodology. Through simulated experiments, our proposed control approach exhibits enhanced performance in accurately tracking target depth, pitch, and heading. Additionally, its adeptness in following intricate trajectories is demonstrated convincingly in simulations.