Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles  

作　　者：Yang YUAN Yimin DENG Sida LUO Haibin DUAN 

机构地区：[1]State Key Laboratory of Virtual Reality Technology and Systems,School of Autonomous Science and Electrical Engineering,Beihang University,Beijing 100083,China [2]School of Mechanical Engineering&Automation,Beihang University,Beijing 100191,China [3]Peng Cheng Laboratory,Shenzhen 518000,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2022年第7期1020-1031,共12页信息与电子工程前沿（英文版）

基　　金：Project supported by the Science and Technology Innovation 2030 Key Project of“New Generation Artificial Intelligence,”China(No.2018AAA0100803);the National Natural Science Foundation of China(Nos.T2121003,U1913602,U20B2071,91948204,and U19B2033)。

摘　　要：We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy flight based pigeon inspired optimization(LFPIO).First,we propose a non-singular fast terminal sliding mode observer(NFTSMO)to estimate the influence of a disturbance,and prove that the observer converges in fixed time using a Lyapunov function.Second,we design an obstacle avoidance strategy based on topology reconstruction,by which the UAV can save energy and safely pass obstacles.Third,we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors.Further,the cost function of each UAV is designed,by which the UAV formation problem is transformed into a game problem.Finally,we develop LFPIO and use it to solve the Nash equilibrium.Numerical simulations are conducted,and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.

关 键 词：Distributed game strategy Unmanned aerial vehicle(UAV) Distributed model predictive control(MPC) Levy flight based pigeon inspired optimization(LFPIO) Non-singular fast terminal sliding mode observer(NFTSMO) Obstacle avoidance strategy 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置] V279[自动化与计算机技术—控制科学与工程]