Receding horizon control for multi-UAVs close formation control based on differential evolution  

作　　者：ZHANG XiangYin, DUAN HaiBin & YU YaXiang National Key Laboratory of Science and Technology on Holistic Control, School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China 

出　　处：《Science China(Information Sciences)》2010年第2期223-235,共13页中国科学（信息科学）（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos. 60975072, 60604009);Aeronautical Science Foundation (Key Program) of China (Grant No. 2008ZC01006);Program for New Century Excellent Talents in University (NCET) of China;"Beijing NOVA Program" Foundation of China (GrantNo. 2007A0017)

摘　　要：Close formation flight is one of the most complicated problems on multi-uninhabited aerial vehicles （UAVs） coordinated control. Based on the nonlinear model of multi-UAVs close formation, a novel type of control strategy of using hybrid receding horizon control （RHC） and differential evolution algorithm is proposed. The issue of multi-UAVs close formation is transformed into several on-line optimization problems at a series of receding horizons, while the differential evolution algorithm is adopted to optimize control sequences at each receding horizon. Then, based on the Markov chain model, the convergence of differential evolution is proved. The working process of RHC controller is presented in detail, and the stability of close formation controller is also analyzed. Finally, three simulation experiments are performed, and the simulation results show the feasibility and validity of our proposed control algorithm.Close formation flight is one of the most complicated problems on multi-uninhabited aerial vehicles （UAVs） coordinated control. Based on the nonlinear model of multi-UAVs close formation, a novel type of control strategy of using hybrid receding horizon control （RHC） and differential evolution algorithm is proposed. The issue of multi-UAVs close formation is transformed into several on-line optimization problems at a series of receding horizons, while the differential evolution algorithm is adopted to optimize control sequences at each receding horizon. Then, based on the Markov chain model, the convergence of differential evolution is proved. The working process of RHC controller is presented in detail, and the stability of close formation controller is also analyzed. Finally, three simulation experiments are performed, and the simulation results show the feasibility and validity of our proposed control algorithm.

关 键 词：uninhabited aerial vehicle （UAV） close formation receding horizon control （RHC） differential evolution （DE） Markov chain 

分 类 号：V279[航空宇航科学与技术—飞行器设计]