高超声速飞行器时间协同再入制导
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摘要
从饱和打击任务需求出发,针对多高超声速飞行器时间协同再入制导问题进行研究,提出时间可控再入制导律和协同再入制导架构,在改善现有制导律实时性、在线约束管理等性能的基础上,重点解决再入飞行时间不可知、不可控问题,最终实现时间协同再入飞行。协同再入制导结构分为两层,其中底层提出了基于神经网络的时间可控再入制导律,以实现再入飞行时间的可知性与可控性为目标;上层根据不同再入阶段特点设计相应的协调函数,生成时间协调信息。该结构适用于集中式或分布式的通讯结构,同时上层协调策略可以根据任务需要进行有针对性的设计与拓展。最后,通过仿真验证了时间可控再入制导律对时间的可控性和协同再入制导结构的有效性。
In this paper,time-coordinated reentry guidance of multi-hypersonic vehicles is investigated in consideration of requirements of saturation attack.To solve the problem of unpredictability and uncontrollability of reentry time and achieve cooperative reentry,a new time-controlled reentry guidance law and cooperative reentry structure are proposed.The reentry guidance law improves real-time performance and constraint management capability of that of existing laws.The structure consists of two layers.To achieve the controllability and anti-interference of reentry flight time,the lower layer adopts the time-controlled reentry law based on the neural network.The upper layer generates time-coordinated information according to different coordination strategies based on characteristics of different reentry phases.The structure is suitable for centralized or distributed communication structure,and the upper coordination function can be designed and expanded according to needs of tasks.Time-controllability of the reentry guidance law and effectiveness of the reentry structure are verified by numerical simulations.
In this paper,time-coordinated reentry guidance of multi-hypersonic vehicles is investigated in consideration of requirements of saturation attack.To solve the problem of unpredictability and uncontrollability of reentry time and achieve cooperative reentry,a new time-controlled reentry guidance law and cooperative reentry structure are proposed.The reentry guidance law improves real-time performance and constraint management capability of that of existing laws.The structure consists of two layers.To achieve the controllability and anti-interference of reentry flight time,the lower layer adopts the time-controlled reentry law based on the neural network.The upper layer generates time-coordinated information according to different coordination strategies based on characteristics of different reentry phases.The structure is suitable for centralized or distributed communication structure,and the upper coordination function can be designed and expanded according to needs of tasks.Time-controllability of the reentry guidance law and effectiveness of the reentry structure are verified by numerical simulations.
引文
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[17]TOMIC S,BEKO M,RUI D.RSS-Based localization in wireless sensor networks using convex relaxation:noncooperative and cooperative schemes[J].IEEE Transactions on Vehicular Technology,2015,64(5):2037-2050.
[18]SHI P,SHEN Q.Cooperative control of multi-agent systems with unknown state-dependent controlling effects[J].IEEE Transactions on Automation Science&Engineering,2015,12(3):827-834.
[19]林涛,刘永才,关成启,等.飞航导弹协同作战使用方法探讨[J].战术导弹技术,2005(2):8-12.LIN T,LIU Y C,GUAN C Q,et al.An investigation into the methods of cooperative engagenment for aerodynamic missile[J].Tactical Missile Technology,2005(2):8-12(in Chinese).
[20]王光伦.高超声速飞行器再入段预测校正制导研究[D].哈尔滨:哈尔滨工业大学,2010:18-19.WANG G L.Predictor-corrector reentry guidance for hypersonic vehicles[D].Harbin:Harbin Institute of Technology,2010:18-19(in Chinese).
[21]PHILLIPS T H.A common aero vehicle(CAV)model,description,and employment guide[R].Albuqerque,New Mexico:Schafer Corp-oration for AFRL and AFSPC,2003.
[22]SUTTON R,BARTO A.Reinforcement Learning:An Introduction[M].Massachusetts:MIT Press,2005:235-304.
[23]DU X,GAO M F.The application of identifying numbers on artificial neural network[J].Computer Systems Applications,2007(2):21-22.
[2]高雁翎,张梦湉,贾晨阳.2016年国外防空反导发展综述[J].战术导弹技术,2017(2):16-20.GAO Y L,ZHANG M T,JIA C Y.Development review of world air and missile defense system in 2016[J].Tactical Missile Technology,2017(2):16-20(in Chinese).
[3]李聪颖,韩蕾,高晓冬,等.再入反舰导弹多弹协同饱和攻击突防最优弹道研究[J].指挥与控制学报,2015,1(1):72-80.LI C Y,HAN L,GAO X D,et al.Study on optimalpenetration trajectories of multi reentry anti-ship missiles for cooperative saturation attack[J].Journal of comma-nd and control,2015,1(1):72-80(in Chinese).
[4]王少平,董受全,李晓阳,等.助推滑翔高超声速反舰导弹多方向协同突防可行性研究[J].指挥控制与仿真,2017,39(2):55-60.WANG S P,DONG S Q,LI X Y,et al.Feasibility study of multi-direction coordinated penetration of the boostglide hypersonic anti-ship missile[J].Command Control and Simulation,2017,39(2):55-60(in Chinese).
[5]JEON I S,LEE J I,TAHK M J.Impact-time-control guidance law for anti-ship missiles[J].IEEE Transactions on Control Systems Technology,2006,14(2):260-266.
[6]赵世钰,周锐.基于协调变量的多导弹协同制导[J].航空学报,2008,29(6):1605-1611.ZHAO S Y,ZHOU R.Multi-missile cooperativeguid-ance using coordination variables[J].Acta Aeronautica et Astronautica Sinica,2008,29(6):1605-1611(in Chinese).
[7]ZHAO S Y,ZHOU R.Cooperativeguidance for multimissile salvo attack[J].Chinese Journal of Aeronautics,2008,21(6):533-539.
[8]MCLAIN T W,BEARD R W.Coordinationvariables,coordination functions,and cooperative timing mission[J].Journal of Guidance Control&Dynamics,2005,28(1):150-161.
[9]张友安,马国欣,王兴平.多导弹时间协同制导:一种领弹-被领弹策略[J].航空学报,2009,30(6):1109-1118.ZHANG Y A,MA G X,WANG X P.Time-cooperative guidance for multi-missiles:A Leader-Follower strategy[J].Acta Aeronautica et Astronautica Sinica,2009,30(6):1109-1118(in Chinese).
[10]赵启伦,陈建,李清东,等.高超武器与常规导弹协同攻击策略可行域研究[J].航空学报,2015,36(7):2291-2300.ZHAO Q L,CHEN J,LI Q D,et al.Feasible region of hypersonic and ballistic missiles’cooperative attack strategy[J].Acta Aeronautica et Astronautica Sinica,2015,36(7):2291-2300(in Chinese).
[11]LU P.Entry guidance:A unifiedmethod[J].Journal of Guidance Control&Dynamics,2014,37(3):713-728.
[12]刘思源,梁子璇,任章,等.高超声速滑翔飞行器再入段制导方法综述[J].中国空间科学技术,2016,36(6):1-13.LIU S Y,LIANG Z X,REN Z,et al.Review of reentry guidance methods for hypersonic gliding vehicles[J].Chinese Space Science and Technology,2016,36(6):1-13(in Chinese).
[13]WANG Z,GRANT M J.Constrained trajectory optimization for planetary entry via Sequential convex programming[C]∥AIAA Atmospheric Flight Mechanics Conference.Reston,VA:AIAA,2017:1-13.
[14]CHENG L,WANG Z,CHENG Y,et al.Multiconstrained predictor-corrector reentry guidance for hypersonic vehicles[J].Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering,2017:095441001772418.
[15]KURIKI Y,NAMERIKAWA T.Consensus-based cooperative formation control with collision avoidance for a multi-UAV system[C]∥American Control Conference.Piscataway,NJ:IEEE Press,2014:2077-2082.
[16]BRARD R W,MCLAIN T W,GOODRICH M A,et al.Coordinated target assignment and intercept for unmanned air vehicles[J].IEEE Transactions on Robotics&Automation,2002,18(6):911-922.
[17]TOMIC S,BEKO M,RUI D.RSS-Based localization in wireless sensor networks using convex relaxation:noncooperative and cooperative schemes[J].IEEE Transactions on Vehicular Technology,2015,64(5):2037-2050.
[18]SHI P,SHEN Q.Cooperative control of multi-agent systems with unknown state-dependent controlling effects[J].IEEE Transactions on Automation Science&Engineering,2015,12(3):827-834.
[19]林涛,刘永才,关成启,等.飞航导弹协同作战使用方法探讨[J].战术导弹技术,2005(2):8-12.LIN T,LIU Y C,GUAN C Q,et al.An investigation into the methods of cooperative engagenment for aerodynamic missile[J].Tactical Missile Technology,2005(2):8-12(in Chinese).
[20]王光伦.高超声速飞行器再入段预测校正制导研究[D].哈尔滨:哈尔滨工业大学,2010:18-19.WANG G L.Predictor-corrector reentry guidance for hypersonic vehicles[D].Harbin:Harbin Institute of Technology,2010:18-19(in Chinese).
[21]PHILLIPS T H.A common aero vehicle(CAV)model,description,and employment guide[R].Albuqerque,New Mexico:Schafer Corp-oration for AFRL and AFSPC,2003.
[22]SUTTON R,BARTO A.Reinforcement Learning:An Introduction[M].Massachusetts:MIT Press,2005:235-304.
[23]DU X,GAO M F.The application of identifying numbers on artificial neural network[J].Computer Systems Applications,2007(2):21-22.