Design of robust control based on linear matrix inequality and a novel hybrid PSO search technique for autonomous underwater vehicle

The control of Autonomous Underwater Vehicle (AUV) is considered as a challenging problem, mainly due to the AUV's nonlinear and uncertain dynamics. In fact, the underwater vehicles require a robust control scheme in order to maneuver to any given point and track a moving target regardless of external disturbances. The main aim of this work consists of proposing two different designs of a robust control system for the nonlinear model of an AUV. The first controller is a PID that optimizes its gains using a novel hybrid PSO algorithm, combining Sine Cosine Algorithm (SCA) and Levy Flight (LF) distribution. The second one is a state feedback control that uses the Linear Matrix Inequality (LMI) approach to guarantee the closed-loop stability in the sense of the Lyapunov stability theory. The proposed control schemes are developed based on the Linear Parameter Varying (LPV) model to take into account the time-varying nature of AUV. The performance quality of these two controllers is evaluated based on the depth control of an AUV in the presence of parametric uncertainty. In order to assess the trajectory tracking, an attitude control system for the underwater vehicle is also developed using the proposed control methodologies. Finally, the obtained simulation results demonstrate that the proposed PSOSCALF-tuned PID not only shows higher robustness in the presence of parametric uncertainties and disturbances but also gives stunning time-domain performances compared to the LMI-based state feedback control.