Robust Path Following Control of AUVs Using Adaptive Super Twisting SOSMC

Abstract

The path-following control design for an autonomous underwater vehicle (AUV) requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigation. AUV dynamics are highly nonlinear and time-varying, facing unpredictable disturbances due to AUVs operating in deep, hazardous oceanic environments. Consequently, navigation guidance and control systems for AUVs must learn and adapt to the time-varying dynamics of the nonlinear fully coupled vehicle model in the presence of highly unstructured underwater operating conditions. Many control engineers focus on the application of robust model-free adaptive control techniques in AUV maneuvers. Hence, the main goal is to design a novel salp swarm optimization of super twisting algorithm-based secondorder sliding mode controller for the planar path-following control of an AUV through regulation of the heading angle parameter. The finite time for tracking error convergence in the horizontal plane is provided through the control structure architecture, particularly for lateral deviations from the desired path. The proposed control law is designed such that it steers a robotic vehicle to track a predefined planar path at a constant speed determined by an end-user, without any temporal specification. Finally, the efficacy and tracking accuracy are evaluated through comparative analysis based on simulation and experimental hardware-in-loop assessment without violating the input constraints. Moreover, the proposed control law can handle parametric uncertainties and unpredictable disturbances such as ocean currents, wind, and measurement noise.

Keywords

Autonomous underwater vehicle / Super twisting second-order sliding mode control / Salp Swarm optimization / Planar path following control and hardware-in-loop

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