)1 Shanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China;[EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (D.Z. );[EMAIL_ADDRESS] (X.L. )1 Shanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China;[EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (X.L. )1 Shanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China;[EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (X.L. )1 Shanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China;[EMAIL_ADDRESS] (G.L. ); [EMAIL_ADDRESS] (D.Z. );[EMAIL_ADDRESS] (X.L. )1 Shanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai controller, effectively addressing the control instability issues in underwater vehicles caused by actuator saturation and complex environmental disturbances [1]. [PERSON] et al. proposed a model reference adaptive PID control structure with an anti-saturation compensator to address the issue of model uncertainty in autonomous underwater vehicle systems [2]. Fuzzy control is a control method similar to expert systems. [PERSON] et al. proposed a fuzzy logic system to address the issue of unknown inertia matrices in AUV systems [3]. [PERSON] et al. proposed a fuzzy adaptive controller that considers the dynamics of ROV thrusters to improve the trajectory tracking performance of work-class ROVs, using a fuzzy adaptive control algorithm to compensate for changes in system parameters and disturbances [4]. [PERSON] et al. proposed a fuzzy logic system (FLS) to replace the discontinuous switching terms in CSMC to reduce chattering phenomena [5]. Sliding Mode Control (SMC) is often used for trajectory tracking of underwater robots due to its resistance to external disturbances and parameter variations. [PERSON] et al. proposed a method that combines a finite-time observer with adaptive sliding mode control to achieve high-precision robust tracking of underwater vehicles [6]. [PERSON] et al. proposed an Adaptive Sliding Mode Control (ASMC) to construct a dynamic controller that calculates the optimal force and torque based on the output virtual speed. This approach is robust to parameter uncertainties and addresses the issue of flutter [7]. [PERSON] et al. proposed an improved sliding surface has been proposed to address the finite selection problem of exponential parameters, resulting in a controller with better robustness [8]. [PERSON] et al. introduced a double closed-loop sliding mode controller for trajectory tracking control of working-class ROVs, which uses the arctangent function as the switching function of the controller, effectively reducing chattering phenomena [9]. Neural network control (NNC) has emerged as a potent tool for crafting controllers for nonlinear and uncertain systems. [PERSON] et al. proposed a predefined time control strategy using Radial Basis Function Neural Networks (RBFNNs), which effectively approximates external disturbances, thereby enhancing the robustness of the system [10]. [PERSON] et al. proposed an adaptive control scheme based on radial basis function (RBF) neural networks for ROV trajectory tracking. To ensure system stability under actuator saturation, a first-order auxiliary state system was constructed [11]. [PERSON] et al. proposed a neural network-enhanced feedback linearization control framework, which effectively addresses the performance guarantee issues of underactuated AUVs under model uncertainties and disturbances [12]. Each of the methodologies mentioned above has specific limitations. As the complexity of the Remotely Operated Vehicle (ROV) model increases, the effectiveness of proportional-integral-derivative (PID) control decreases significantly.