生物启发自治水下机器人轨迹跟踪控制研究

The underwater environment is very complicated, and AUV is a strongly coupled system with nonlinear and uncertainty,so tracking control research of AUV is becoming more and more challenging..In this project three-dimensional tracking control of AUV is studied for complicated envirment with ocean current and multi-nterference. Firstly, underwater noise interference is removed by using multi-sensor information fusion technology, and underwater position information of AUV is acquired accurately; Then the reference virtual tracking velocity of AUV is obtained by using the bio-inspired neurdynamics model, the problem of tracking speed jump is resolved and the thruster control constraints of AUV is guaranteed; On the basis of process above, AUV tracking control law can be obtained adaptively by the sliding mode control algorithm, and tracking control of AUV is realized accrately after model uncertainty is eliminated; Finally the effectiveness and efficiency of the proposed control strategy (the bio-inspired neurdynamics based tracking control algorithm) are demonstrated through "Maritime Number one" AUV experiment system.

深海环境的复杂性，水下机器人自身的强耦合、非线性及模型不确定特性，使得水下机器人轨迹跟踪控制成为一个十分具有挑战性的研究领域。.本项目针对无缆自治水下机器人AUV(Autonomous Underwater Vehicles)，研究多干扰复杂海流环境下AUV三维立体轨迹跟踪控制技术。首先，应用多传感器信息融合技术消除水下噪音干扰、获取准确的机器人水下位置信息；接着利用生物启发神经动力学模型产生渐变的AUV参考虚拟跟踪速度，克服自治水下机器人跟踪速度跳变，满足AUV推进器最大推力约束；在此基础上应用自适应滑模控制算法产生AUV的轨迹跟踪控制律，消除模型不确定影响，实现自治水下机器人稳定、准确的轨迹跟踪控制；最后，利用实验室"海事一号"自治水下机器人系统，验证所提生物启发自治水下机器人轨迹跟踪控制方法的有效性。

本项目针对无缆自治水下机器人AUV(Autonomous Underwater Vehicles)，研究多干扰复杂海流环境下AUV三维立体轨迹跟踪控制技术。应用多传感器信息融合技术消除水下噪音干扰、获取准确的机器人水下位置信息；利用生物启发神经动力学模型产生渐变的AUV参考虚拟跟踪速度，克服自治水下机器人跟踪速度跳变，满足AUV推进器最大推力约束；在此基础上应用自适应滑模控制算法产生AUV的轨迹跟踪控制律，消除模型不确定影响，实现自治水下机器人稳定、准确的轨迹跟踪控制；利用实验室“海事金枪鱼号”自治水下机器人系统，验证所提生物启发自治水下机器人轨迹跟踪控制方法的有效性。