Experimental and Numerical Study on Trajectory Tracking of Remotely Operated Vehicles Involved in Cleaning Aquaculture Vessels

Efficient cleaning is crucial in aquaculture vessels; however, Remotely Operated Vehicles (ROVs) encounter difficulties in regard to trajectory tracking within confined chambers, because of structural nonlinearities and environmental disturbances. To address these challenges, this paper proposes a multi-scale dynamic sliding mode adaptive control (MDSMAC) scheme to compensate for the effects of structural nonlinearities and external disturbances, achieving precise trajectory tracking. Based on a six-degree-of-freedom motion model, an adaptive multi-scale sliding mode control mechanism is designed, enabling the system to adapt to scale variations and environmental disturbances, enhancing control accuracy and robustness. The asymptotic stability of the system is rigorously proven using the second Lyapunov method. The numerical simulation results show that the proposed method exhibits superior robustness to external disturbances and high precision in complex environments, confirming its long-term stability. Water tank experiments were conducted to further evaluate the trajectory tracking performance of the method under nonlinear system control. The results show the high level of feasibility and strong potential of the approach for practical applications.