基于障碍物速度位置机会约束无人机MPC防撞策略  

MPC collision avoidance strategy of UAV based on obstacle velocity position chance constraint

作　　者：郑淦专 马锋 ZHENG Ganzhuan;MA Feng(Qingyuan Polytechnic,Qingyuan 511500,China;School of Mechanical and Power Engineering,Henan University of Technology,Jiaozuo 454003,China)

机构地区：[1]清远职业技术学院,广东清远511500 [2]河南理工大学机械与动力工程学院,河南焦作454003

出　　处：《飞行力学》2024年第6期23-30,共8页Flight Dynamics

基　　金：2020年广东省普通高校青年创新人才项目(2020WQNCX218)。

摘　　要：为了解决编队过程中的不确定性,提升避障精度,提出一种基于障碍物速度位置机会约束无人机的模型预测控制防撞策略。模型预测控制可以在约束优化框架中考虑多个防撞约束,综合考虑速度约束和位置约束的优势,引入了一种基于障碍物速度机会约束策略,从而能够有效描述速度和相关位置的不确定性,由于与位置机会约束相结合,因此在噪声环境中对高速障碍物能够实现鲁棒避障。最后将提出方法进行数值仿真对比验证,结果证明所提方法能够有效提升避障精度。In order to solve the uncertainty in the formation process and improve the accuracy of obstacle avoidance,a collision avoidance strategy of UAV model predictive control based on obstacle speed and position chance constraints was proposed.The model predictive control could consider multiple collision avoidance constraints in the constraint optimization framework.Considering the advantages of speed constraints and position constraints,a strategy based on obstacle speed chance constraints was introduced,which could effectively describe the uncertainty of speed and related positions.Due to the combination with position chance constraints,it could achieve robust obstacle avoidance for high-speed obstacles in noisy environments.Finally,the proposed method was compared and verified through the numerical simulation.The results show that the proposed method can effectively improve obstacle avoidance accuracy.

关 键 词：无人机 编队飞行 模型预测控制 防撞控制 机会约束 

分 类 号：V279[航空宇航科学与技术—飞行器设计] V249.1