Robust Yaw Angle Control of an AUV: Terminal Sliding Manifold Based Optimized Super‐Twisting Algorithm

This paper investigates the attitude control problem of an autonomous underwater vehicle (AUV) in the presence of parameter model uncertainties, dynamic coupling effects and external disturbances. To address attitude control challenges, the control scheme aims to maintain the desired orientation, handle actuator nonlinearities and ensure stable, fast and tracking performance. So, the main focus is to design a robust adaptive control scheme to ensure prescribed tracking accuracy with predefined convergence time while avoiding singularities in the vehicle model and enhancing robustness. The finite time error convergence and robustness are accomplished via a non‐singular terminal sliding manifold, a continuous equivalent control term, and a super‐twisting algorithm with online uncertainty and disturbance estimator (UDE). The notable feature of the proposed design is that it neither requires an accurate vehicle model nor requires prior knowledge of an upper bound on uncertainties in the dynamic parameters of an AUV. An adaptive super‐twisting algorithm is integrated with an improved aquila optimization for regulating the yaw angle of the AUV. Also, reduce chattering, reaching time and handle complex oceanic scenarios effectively. Further, UDE is deployed to resolve the influence of uncertain hydrodynamic coefficients, payload variations and exogenous disturbances such as ocean waves, currents and measurement noises. In addition, the thruster model non‐linearity, like a non‐symmetric dead zone with an unpredictable parameter, is smoothly handled via an auxiliary dynamic compensator. Extensive simulation results, along with experimental validation on an AUV equipped with cross‐type rudders, confirm that the proposed method achieves superior tracking accuracy, faster convergence and enhanced robustness under severe environmental disturbances and actuator non‐linearities.