英文摘要 | Underwater vehicle-manipulator systems (UVMSs) are valuable tools for the exploration and development of the ocean environment, and has been widely used for applications such as the salvage of submerged objects, underwater archaeology, rescue and salvage operations, and fishing. The present thesis focuses on the system design of a fippers-propelled UVMS (F-UVMS), underwater terrain prediction and following control, coordinated control of underwater biomimetic vehicle and manipulator, and autonomous control for grasping objects underwater current disturbance. The main contents of the present thesis are as follows:
First, to perform underwater autonomous manipulation tasks, the design method of the F-UVMS and the development of a first prototype are presented. A fippers propulsor was designed and integrated to the UVMS. According to the requirements of underwater manipulation tasks, a four-degrees of freedom (DOF) underwater manipulator and an underwater sensor system are mounted on the underwater vehicle. Furthermore, an onboard control system and software system based on Robot Operating System (ROS) are also developed. The reliability and validity of the F-UVMS is analyzed by system integration and experiments.
Second, an underwater terrain predicting and following control method is proposed to perform underwater terrain navigation with UVMS in unknown environments. As a first step, an underwater terrain predicting method based on long short-term memory network (LSTM) and nonlinear prediction model is put forward. Then, by virtue of the predicted underwater terrain information, an optimal method based on nonlinear model predictive control (NMPC) for underwater terrain following is presented. In addition, the continuation/general minimum residual (C/GMRES) algorithm is used to improve the computational efficiency of the NMPC. ROS-based simulation experiments and sea experiments for underwater terrain predicting and following control were conducted, and results are used to verify the effectiveness of the proposed underwater terrain predicting and following control method.
Third, a vehicle-manipulator coordinated control method based on non-singular terminal sliding mode control (NTSMC) is proposed to address the UVMS dynamic coupling problem. An improved NTSMC (I-NTSMC) was first formulated as the main controller. A sliding mode reaching motion control law, an adaptive tracking differentiator, and a state observer are integrated into the I-NTSMC to relieve the chattering
phenomenon and speed up convergence. Then, the Newton-Enler model is formulated to estimate the disturbance imposed on an underwater biomimetic vehicle generated by instantaneous manipulator motion. The estimated disturbance is compensated for the main controller. The effectiveness of the proposed method was verified through experiments on an underwater autonomous opening door and grasping objects using UVMS under free-floating status.
Fourth, focusing on searching for underwater objects and grasping them in a water current disturbance environment, an objects searching strategy and autonomous grasping control method with water current disturbance compensation are studied. A search strategy for underwater objects is proposed, combining underwater terrain navigation and obstacle detection information using collision obstacle sonar. Then, an autonomous grasping control framework is presented, which consists of a radial basis function neural network based disturbance observer (RBF-DOB), LSTM-based predictive model network, NMPC, and Newton-Enler model. The RBF-DOB is formulated to estimate the water current disturbance. The LSTM-based predictive model network is composed of a state prediction network and a water current disturbance prediction network, which can be used to predict UVMS state sequences underwater current disturbance. The UVMS state sequences were used to generate optimal control with the help of NMPC. Meanwhile, the manipulator motion disturbance is considered as feedforward compensation. ROS-based underwater simulations for objects searching and autonomous grasping were conducted to demonstrate the effectiveness of the proposed method. |
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