CAJ | 학술논문

针对风场干扰下多无人机(UAV)编队的控制问题，提出一种基于一致性卡尔曼滤波的多无人机编队控制算法。根据一致性卡尔曼滤波算法，测量每架无人机的风场干扰误差，预测控制编队中各机的相对位置；设置编队的中心关键点，并利用总卡尔曼滤波器调整其位置，由此实现了一致性卡尔曼滤波算法与航迹修正相结合解决风场干扰下多无人机编队的控制问题；并将该算法应用到轨迹跟踪问题，从而实现编队对复杂航迹的实时跟踪。仿真结果表明，文中提出的算法具有很好的灵活性、鲁棒性、可靠性和可伸缩性。
침대풍장간우하다무인궤(UAV)편대적공제문제，제출일충기우일치성잡이만려파적다무인궤편대공제산법。근거일치성잡이만려파산법，측량매가무인궤적풍장간우오차，예측공제편대중각궤적상대위치；설치편대적중심관건점，병이용총잡이만려파기조정기위치，유차실현료일치성잡이만려파산법여항적수정상결합해결풍장간우하다무인궤편대적공제문제；병장해산법응용도궤적근종문제，종이실현편대대복잡항적적실시근종。방진결과표명，문중제출적산법구유흔호적령활성、로봉성、가고성화가신축성。
With respect to the problem of controlling unmanned aerial vehicles (UAVs) formation under wind interference, the UAV formation control algorithm based on consensus Kalman filtering algorithm was proposed. Firstly the wind field measurement errors of each UAV can be estimated and the relative position of each UAV in the formation can be predicted by using consensus-based Kalman filtering algorithm. Secondly the formation center is set and it’s position can be modified by the center Kalman filter. Then the control algorithm is achieved by combining the consensus-based Kalman filtering algorithm and the trajectory correction to solve the problem of UAVs formation under wind interference. At last, this algorithm is applied into the trajectory tracking problem and it can realized the timely tracking of complex formation trajectory. The simulation was computed to show the flexibility, robustness, reliability and scalability of the mentioned algorithm.