【摘要】 针对复杂湖面环境干扰下的无人艇自主航行控制问题，设计了一种有效的无人艇航迹跟踪控制系统。该系统从航迹跟踪控制算法、数据融合处理、上位机监控三个部分展开设计。在算法设计层面，将航迹跟踪控制问题分为外环和内环两部分，外环部分提出了一种自适应视线(line of sight, LOS)制导算法，以求解目标航向角作为航向控制器的输入；内环部分设计了无模型自适应比例积分微分(model free adaptive-proportion integration differentiation, MFA-PID)航向控制器，以实现无人艇稳定的航行。在数据处理层面，采用卡尔曼滤波算法对传感器信息进行融合，实现了对无人艇位置和姿态信息的准确估计。在监控层面，设计了一种可视化上位机软件，实时监测无人艇航行状态，保证航行安全。最后，利用实艇进行湖测实验，验证了该控制系统的有效性，结果表明该系统具备在内湖执行任务的能力以及应对复杂环境干扰的能力。更多还原

【Abstract】 An effective unmanned surface vehicle trajectory tracking control system was designed for the problem of autonomous navigation control of unmanned surface vehicle under complex lake interference environment. The system had been designed in three parts: track tracking control algorithm, data fusion processing, and upper computer monitoring. At the algorithm design level, the trajectory tracking control problem had been divided into two parts. The outer loop part proposed an adaptive line of sight(LOS) guidance algorithm to solve the target heading angle as the input of the heading controller. The inner loop part designed a model free adaptive PID heading controller to achieve stable navigation of the unmanned surface vehicle. At the data processing level, the Kalman filter algorithm had been used to fuse the sensor information to achieve accurate estimation of the position and attitude information of the unmanned surface vehicle. At the monitoring level, a visualization upper computer software had been designed to monitor the navigation status of the unmanned surface vehicle in real time to ensure navigation safety. Finally, the effectiveness of the control system has been verified by conducting lake test experiments using a real boat, and the results have shown that the system has the ability to perform tasks in the inner lake as well as the ability to cope with complex environmental interference.更多还原