Underwater Dynamic Target Tracking of Autonomous Underwater Vehicle Based on MPC Algorithm

Yali Wei, Daqi Zhu, Zhenzhong Chu
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引用次数: 11

Abstract

In this paper, a dynamic target tracking method based on model predictive control (MPC) algorithm was proposed for autonomous underwater vehicle (AUV). Through the processing of AUV sonar images, the dynamic target can be identified and located in real time. Then the Kalman filter was used to reasonably predict the position of the dynamic target at the next moment. Finally, MPC algorithm is applied to track the dynamic target online and follow it. Through experiments, the actual position of the target was obtained. And by simulation, MPC can accurately track dynamic targets, which has also been proved. This algorithm can not only track the trajectory, but also track the dynamic target, which meets the practical requirements
基于MPC算法的自主水下航行器水下动态目标跟踪
提出了一种基于模型预测控制(MPC)算法的自主水下航行器动态目标跟踪方法。通过对水下航行器声呐图像的处理,实现对动态目标的实时识别和定位。然后利用卡尔曼滤波合理预测下一时刻动态目标的位置。最后,应用MPC算法对动态目标进行在线跟踪和跟踪。通过实验,得到了目标的实际位置。仿真结果也证明了MPC能够准确跟踪动态目标。该算法既能跟踪轨迹,又能跟踪动态目标,满足实际要求
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