Guohua Xu’s research while affiliated with Huazhong University of Science and Technology and other places

In this study, we present a novel dual-loop robust trajectory tracking framework for autonomous underwater vehicles, with the objective of enhancing their performance in underwater searching tasks amidst oceanic disturbances. Initially, a real-world AUV experiment is conducted to validate the efficacy of a cross-rudder AUV configuration in maintaining sailing angle stability during the diving stage, which exhibits a strong capability for straight-line sailing. Building upon the experimental findings, we introduce a state-transform-model predictive guide law to compute the desired velocity for the dynamics loop. This guide law dynamically adjusts the controller across varying depths, thereby reducing model predictive control (MPC) computation while optimizing timing without compromising precision or convergence speed. Subsequently, we incorporate a sliding mode controller with a prescribed disturbance observer into the velocity control loop to concurrently enhance the robustness and convergence rate of the system. This innovative amalgamation of controllers significantly improves tracking precision and convergence rate, while also alleviating the computational burden—a pervasive challenge in AUV MPC control. Finally, various condition simulations are conducted to validate the robustness, effectiveness, and superiority of the proposed method. These simulations underscore the enhanced performance and reliability of our proposed trajectory tracking framework, highlighting its potential utility in real-world AUV applications.

To address the search-and-docking problem in multi-stage prescribed performance switching (MPPS) scenarios, this paper presents a novel compound control method for three-dimensional (3D) underwater trajectory tracking control of unmanned underwater vehicles (UUVs) subjected to unknown disturbances. The proposed control framework can be divided into two parts: kinematics control and dynamics control. In the kinematics control loop, a novel parallel model predictive control (PMPC) law is proposed, which is composed of a soft-constrained model predictive controller (SMPC) and hard-constrained model predictive controller (HMPC), and utilizes a weight allocator to enable switching between soft and hard constraints based on task goals, thus achieving global optimal control in MPPS scenarios. In the dynamics control loop, a finite-time terminal sliding mode control (FTTSMC) method combining a finite-time radial basis function neural network adaptive disturbance observer (RBFNN-FTTSMC) is proposed to achieve disturbance estimation and fast convergence of velocity tracking errors. The simulation results demonstrate that the proposed PMPC-FTTSMC approach achieved an average improvement of 33% and 80% in the number of iterations compared with MPC with sliding mode control (MPC-SMC) and traditional MPC methods, respectively. Furthermore, the approach improved the speed of response by 35% and 44%, respectively, while accurately achieving disturbance observation and enhancing the system robustness.

This paper proposes a novel motion-tracking control methodology for an underwater cable-driven parallel mechanism (CDPM) that achieves calculation of dynamic tension constraint values, tension planning, parameter linearization, and motion tracking. The control objective is divided into three sub-objectives: motion tracking, horizontal displacement suppression, and cable-tension restriction. A linear model predictive control (LMPC) method is designed to plan cable tensions for motion-tracking and displacement suppression. The robust adaptive backstepping controller converts cable tension into winch speed based on the joint-space method and command filtering. Moreover, the X−swapping method is used to linearize and identify the time−varying nonlinear parameters. An essential prerequisite for restricting cable tension is to obtain cable-tension constraint values. A novel dynamic minimum tension control (DMTC) method, based on the equivalent control concept, is proposed for this aim. The DMTC can adaptively obtain the lower cable-tension threshold through the platform posture and motion status, anchor distribution position, and cable integrity status. Compared to traditional fixed tension constraint values, DMTC can more effectively cope with sudden changes in cable tension than fixed tension constraints. Finally, several simulations are carried out to verify the effectiveness and robustness of the proposed approach.

This paper investigates the problem of path following with prescribed performance for autonomous underwater vehicles subjects to unknown actuator dead-zone nonlinearity. To cope with this practical problem abstracted from hydrodynamic noise measurement, an adaptive command filtered backstepping method with actuator dead-zone compensation is proposed. By introducing a damped exponential barrier functions, new tracking errors are defined to satisfy the prescribed performance requirements. The path following control method is theoretically based on the command filtered backstepping technique for handling the complexity explosion problem attribute to the repeating derivations. Moreover, the filter compensation mechanism is designed to eliminate the negative effect of the filter errors. To deal with the actuator dead-zone nonlinearity, a fuzzy logic system based dead-zone compensation method is developed that dose not need the inverse of the dead-zones. Numerical simulations are conducted to demonstrate the theoretical analysis, and the usefulness and potential of the new design scheme is revealed.

In this article, a novel adaptive robust trajectory tracking framework with roll control is created for a X-Rudder autonomous underwater vehicle (XAUV) subjects to system nonlinearities, unknown disturbances, and complex actuator dynamics. First, a roll control law is introduced to the kinematics control loop, and the hyperbolic-tangent Line-of-sight (HLOS) based guidance law is proposed, which considers the three-dimensional (3D) tracking errors, collaboratively governing heading, pitch, and roll. Second, a novel super-hyperbolic switching algorithm (SHSA) based sliding mode controller is deployed in the dynamics control loop to achieve trajectory tracking and roll control, which combines the advantages of the two hyperbolic functions, avoids the chattering problem while achieving rapid convergence, this enhancing the control accuracy and stability simultaneously. Besides, the robustness to unknown disturbances (including environmental disturbances and propeller reaction torque) is enhanced by nonlinear disturbance observers. To tackle the potential instabilities from compound actuator dynamics, an anti-windup compensator is resorted to compensate for the control truncation of propulsion system, and an optimal X-Rudder allocator is utilized to solve the rudder angle assignment problem with multiple constraints. Finally, comparative numerical simulations are carried out to verify the effectiveness of proposed controller.