Control method for multi-UAVs cooperative obstacle avoidance

被引：0

作者：

Zhang L. ^{[1
]}

Ru C. ^{[2
]}

Zhou H. ^{[2
]}

机构：

[1] Department of Theory and Training, Air Force Xi'an Flight College, Xi'an

[2] College of Aeronautics and Aerospace Engineering, Air Force Engineering University, Xi'an

来源：

Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2016年 / 47卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Extended Kalman filter; Model predictive control; Obstacle avoidance; UAVs cooperation;

D O I：

10.11817/j.issn.1672-7207.2016.01.017

中图分类号：

学科分类号：

摘要：

For solving the problem of multi-UAVs (multi-unmanned aerial vehicles) cooperative obstacle avoidance in dynamic environment, a method for controller design in combination with the extended Kalman filter (EKF) and model predictive control (MPC) was proposed. Firstly, distributed architecture for UAV cooperative obstacle avoidance, the motion model of UAV and the communication topology were established, respectively. Then the EKF algorithm was used to predict the trajectory of dynamic obstacle, and an information compensation rule was designed. Afterwards, based on the model predictive control (MPC) method, the controller for UAV obstacle avoidance was designed. The results show that the proposed EKF method can predict the trajectory of dynamic obstacle correctly, and that the cooperation between the UAVs can reduce the predictive errors effectively. © 2016, Central South University of Technology. All right reserved.

引用

页码：114 / 122

页数：8

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