| 英文摘要 | Underwater biomimetic vehicle plays an important role in many practical applications due to its higher efficiency and better maneuverability. Furthermore, the vehicle propelled by two undulatory fins is a typical underwater biomimetic vehicle. This thesis focuses on the system design, modeling, control and path planning of the vehicle propelled by two undulatory fins. The main content of this thesis is described as follows. Firstly, based on the biomimetic mechanism and system control requirements, we designed a prototype of swimming vehicle with two undulatory fins, an FPGA-based driving system, an ARM-Linux-based real-time control system, and a sensor system based on inertial units, respectively. Then, by integrating the above elements, an experimental system and a remote control platform were designed. Secondly, by studying the motion characteristics of undulatory fins, an adjusting algorithm for the control parameters of the undulatory fin is proposed. By considering the coordination control methods of two undulatory fins, several swimming motion modes are developed, such as marching mode, receding mode, rotating mode, side-swaying motion mode etc. On the basis of these motion modes, an obstacle avoidance strategy is proposed by integrating the swimming motion mode switch and the finite-automata approach. Thirdly, by considerable open-loop swimming control experiments, a reasonable model simplification method is proposed based on experimental data analysis. Then by recursive weighted least square method and neural network approach, several input-output models were developed for the typical swimming motion modes. Fourthly, a yaw angle and speed control method for the vehicle was proposed by combining fuzzy control and PID control. In addition, by improving the controller structure of vehicle, a model-based feed-forward compensation control algorithm is proposed to increase the system responding speed. Fifthly, a Bezier curve based 3D path planning algorithm is proposed by considering the path planning requirements and mechanical constraints of the vehicle. Moreover, according to the requirements of online planning, secondary planning and obstacle avoidance, the proposed path planning algorithm is improved. Finally, the whole thesis is summarized and future work is addressed. |
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