The paper showcases a data-driven nonlinear adaptive controller design employing an unfalsification approach to attain optimal estimates for unknown parameters in an Autonomous Underwater Vehicle (AUV). These estimates obtained are applied to the controller for enabling precise trajectory tracking. The controller design presented is capable of adapting to parametric changes and uncertainties while fulfilling the desired performance criteria by an effective parameter update method of unfalsification. The results are validated through simulations conducted using MATLAB/SIMULINK.
Keywords: Adaptive control, Autonomous Underwater Vehicle, Data-driven control, Unfalsified control,