Model Reference Adaptive Fuzzy Controller of a 6-DOF Autonomous Underwater Vehicle

Currently, efficient ocean health monitoring using an autonomous underwater vehicle (AUV) must take into account the complex characteristics of the ocean, the non-linear model of the AUV, high coupling, and unknown parameters that can change over time. In this paper, a Model Reference Adaptive Fuzzy Controller (MRAFC) is proposed for the control of navigation trajectories of a 6-DOF AUV. First, the proposed AUV design for monitoring the Peruvian coastline is summarized. Later the non-linear model of the AUV and the design of the MRAFC represented by the fuzzy Takagy-Sugeno model are presented. Additionaly, Lyapunov theories are used to provide an asymptotic follow-up to a reference trajectory for the model with uncertain parameters or that changes slowly over time. Simulation results show that the proposed controller stabilizes the system and allows a more robust and faster AUV displacement than other traditional controllers.