Formation Control of Unmanned Surface Vehicleswith Position Estimation Algorithm
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摘要: 针对因定位精度导致多无人船编队队形不稳定的问题，提出一种结合扩展卡尔曼滤波的领航-跟随编队控制策略，以提高定位精度形成稳定的编队队形。建立无人船系统数学模型，分析基于领航-跟随法的多无人船编队的数学模型；根据领航-跟随法设计编队控制律，并结合李雅普诺夫函数证明系统稳定性，针对编队中所需的位置信息，利用扩展卡尔曼滤波(EKF)融合GPS与IMU两部分数据，提高定位精度；进行多无人船编队以及队形变换等仿真实验，并对引入EKF后的实验数据进行分析。结果表明，编队控制器及位置估计算法可有效控制跟随无人船形成稳定的编队队形，且变换队形后，可迅速且稳定地完成队形重构。Abstract: Because the formation of USVs(unmanned surface vehicles) is unstable due to the positioning accuracy, a leader-follower formation control strategy combined with the extended Kalman filteringstrategy is proposed to improve the positioning accuracy and form a stable formation. First, this paper builds a mathematical model of the unmanned surface vehicle and focuses on analyzing the formation model of multiple USVs based on the leader-followerformation control strategy. Then, the formation controller is designed according to the leader-follower formation control strategy. The stability of the USV is proved by using the Lyapunov function. For the position information required by the formation, the EKF (the extended Kalman filter) is used to fuse the data of GPS and IMU to improve the positioning accuracy. Finally, the simulationof USVformation and its transformation are carried out. The experimental data after introducing the EKF is analyzed. The simulation results show that the formation controller and the position estimation algorithm can effectively control the formation of stableUSVs. The formation can bereconstructed quickly and stably after transformation.
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表 1 误差参数
误差项 数值 加速度计零偏 10−4 g 加速度计安装误差 5 °/s 加速度计白噪声 10−5 g 陀螺仪零偏 0.03 °/h 陀螺仪安装误差 1 °/s 陀螺仪白噪声 0.01 °/h 
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