The trajectory optimization of Space Maneuver Vehicle based-on Dynamic Neural Network
详细信息 查看官网全文
- 英文论文题名：The trajectory optimization of Space Maneuver Vehicle based-on Dynamic Neural Network
- 论文作者：Sainan Ren ; Senchun Chai ; Baihai Zhang ; Fenxi Yao ; Lingguo Cui
- 英文论文作者：Sainan Ren ; Senchun Chai ; Baihai Zhang ; Fenxi Yao ; Lingguo Cui ; Beijing institute of technology
- 年：2017
- 作者机构：Beijing institute of technology;
- 英文论文关键词：SMV vehicle ; Trajectory optimization ; Neural network ; Dynamic
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP183;V448
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：854k
- 原文格式：D
- 会议级别：全国
摘要
In order to solve the problem of trajectory optimization of Space Maneuver Vehicle(SMV), a dynamic neural network method is introduced. Combined with neural network and Pontryagin's maximum principle, the method is able to approximate the optimal solution by neural network. At the same time, with the dynamic process, the problem of guessing covariates' initial value in traditional indirect method has been solved fairly well. In this work, the principle of the Dynamic Neural Network(DNN) optimal algorithm has been given and the optimization process has been described in detail. The simulation results indicated that using Dynamic Neural Network optimal algorithm can avoid guessing the covariates' initial value and satisfy the real-time requirements. Moreover, it has a higher accuracy solution.
In order to solve the problem of trajectory optimization of Space Maneuver Vehicle(SMV), a dynamic neural network method is introduced. Combined with neural network and Pontryagin's maximum principle, the method is able to approximate the optimal solution by neural network. At the same time, with the dynamic process, the problem of guessing covariates' initial value in traditional indirect method has been solved fairly well. In this work, the principle of the Dynamic Neural Network(DNN) optimal algorithm has been given and the optimization process has been described in detail. The simulation results indicated that using Dynamic Neural Network optimal algorithm can avoid guessing the covariates' initial value and satisfy the real-time requirements. Moreover, it has a higher accuracy solution.
In order to solve the problem of trajectory optimization of Space Maneuver Vehicle(SMV), a dynamic neural network method is introduced. Combined with neural network and Pontryagin's maximum principle, the method is able to approximate the optimal solution by neural network. At the same time, with the dynamic process, the problem of guessing covariates' initial value in traditional indirect method has been solved fairly well. In this work, the principle of the Dynamic Neural Network(DNN) optimal algorithm has been given and the optimization process has been described in detail. The simulation results indicated that using Dynamic Neural Network optimal algorithm can avoid guessing the covariates' initial value and satisfy the real-time requirements. Moreover, it has a higher accuracy solution.
引文
[1]Yuzhi Xiao,Junyong Yi,Baoheng Zhang and Zhiwen He,”Research on mission planning and overall performance of space maneuver vehicle simulation system”,China Aerospace Safety Conference,2015.(in chinese)
[2]Jiawei Zhang,Kemao Ma,Guizhi Meng and Shuang Tian,”Spacecraft maneuvers via singularity-avoidance of control moment gyros based on dual-mode model predictive control,”IEEE Transactions on Aerospace and Electronic Systems,vol.51,no.4,pp.2546-2559,2015.
[3]Zhongda Xu,Xu Cha,Yongsheng Wang and Haocheng Zhang,”Research on technology of aerodynamic force support coplanar orbit of Space maneuver flight”,The Eighth National Hypersonic Technology Conference,2015.(in chinese)
[4]Xin Jiang,”Research on transfer alignment of strapdown inertial navigation system for space vehicle[M]”,Harbin Institute of Technology,2012.(in chinese)
[5]Cong Cheng,Chengqi Guan and Hongliang Shi,”A survey of direct numerical methods for trajectory optimization”,Control Technology of Tactical Missile,2009,31(2):33-40.
[6]Afshin Rahimi,Krishna Dev Kumar and Hekmat Alighanbari,”Particle swarm optimization applied to spacecraft reentry trajectory,”Journal of Guidance,Control,and Dynamics,vol.36,no.1,pp.307-310,2012.
[7]Robert Windhorst,Mark Ardema and Jeffrey Bowles,”Minimum heating reentry trajectories for advanced hypersonic launch vehicles”,ser.Guidance,Navigation,and Control and Co-located Conferences.American Institute of Aeronautics and Astronautics,1997,doi:10.2514/6.1997-3535.
[8]Ying Nan,Guo Qiang Huang,Yu Ping Lu and Ping Gong,”Global 4-D trajectory optimization for spacecraft”,Science China Technological Sciences,2010,Vol.53(8),pp.2097-2101.
[9]John T.Betts,”Survey of Numerical Methods for Trajectory Optimization[J]”,Journal of Guidance,Control,and Dynamics,1998,21(2):193-207.
[10]David G.Hull,”Conversion of optimal control problems into parameter optimization problems[J]”,Journal of Guidance,Control,and Dynamics.1997,20(1):57-60.
[11]Brian C.Fabien,”Some tools for the direct solution of optimal control problems[J]”,Advances in Engineering Software,1998,29(1):45-61.
[12]David Marcelo Garza,”Application of automatic differentiation to trajectory optimization via direct multiple shooting[D]”,Austin,Texas:The University of Texas at Austin,2003.
[13]Gang Chen,Ying Hu,Ziming Wan,Min Xu and Shilu Chen,”Optimization design on RLV reentry trajectory based on genetic algorithm”,Journal of Solid Rocket Technology,2006,29(4):235-238.
[14]Dingni Zhang and Yi Liu,”Reentry trajectory optimization based on proved genetic algorithm and sequential quadratic programming[J]”,Aerospace Control,2009,27(6):8-13.
[15]Qingzhen Zhang,Zhenbo Wang,Fei Tao,Bhaba R.Sarker,Lin Cheng and Shantung Tu,”Design of Optimal Attack-Angle for RLV Reentry Based on Quantum Particle Swarm Optimization”,Advances in Mechanical Engineering,2014,Vol.2014.
[16]Jiang Zhao,Rui Zhou and Xuelian Jin,”Progress in reentry trajectory planning for hypersonic vehicle[J]”,Journal of Systems Engineering and Electronics,2014,25(4):627-639.
[17]Gonzalo Joya,Miguel Atencia and Francisco Sandoval,”Hopfield neural networks for optimization:study of the different dynamics”,Neurocomputing.2002,43(1-4):219-237.
[18]Miguel Atencia and Gonzalo Joya,”Hopfield networks:from optimization to adaptive control”,International Joint Conference on Neural Networks,2015.
[19]Bin Zhang,Shiyi Guan and Shilu Chen,”Modified ant colony algorithm-based reentry trajectory optimization for suborbital launch vehicle[J]”,Journal of Astronautics,2011,32(6):1244-1248.
[20]Zachary J Kiyak,Roy J Hartfield and Timothy W Ledlow,”Missile trajectory optimization using a modified ant colony algorithm”,Proc.of the Aerospace Conference,2014:1-8.
[21]Shouwei Gao,Yeqing Yang and Weidong Zhang,”Trajectory Planning for Cruise Missile in Three-Dimensional Space Based on Improved Ant Colony Algorithm”,Journal of Shanghai Jiaotong University,2010.
[22]Runqi Chai,”Violation learning deferential evolution-based hp-adaptive pseudospectral method for trajectory optimization of Space Maneuver Vehicle”,IEEE,2016.
[2]Jiawei Zhang,Kemao Ma,Guizhi Meng and Shuang Tian,”Spacecraft maneuvers via singularity-avoidance of control moment gyros based on dual-mode model predictive control,”IEEE Transactions on Aerospace and Electronic Systems,vol.51,no.4,pp.2546-2559,2015.
[3]Zhongda Xu,Xu Cha,Yongsheng Wang and Haocheng Zhang,”Research on technology of aerodynamic force support coplanar orbit of Space maneuver flight”,The Eighth National Hypersonic Technology Conference,2015.(in chinese)
[4]Xin Jiang,”Research on transfer alignment of strapdown inertial navigation system for space vehicle[M]”,Harbin Institute of Technology,2012.(in chinese)
[5]Cong Cheng,Chengqi Guan and Hongliang Shi,”A survey of direct numerical methods for trajectory optimization”,Control Technology of Tactical Missile,2009,31(2):33-40.
[6]Afshin Rahimi,Krishna Dev Kumar and Hekmat Alighanbari,”Particle swarm optimization applied to spacecraft reentry trajectory,”Journal of Guidance,Control,and Dynamics,vol.36,no.1,pp.307-310,2012.
[7]Robert Windhorst,Mark Ardema and Jeffrey Bowles,”Minimum heating reentry trajectories for advanced hypersonic launch vehicles”,ser.Guidance,Navigation,and Control and Co-located Conferences.American Institute of Aeronautics and Astronautics,1997,doi:10.2514/6.1997-3535.
[8]Ying Nan,Guo Qiang Huang,Yu Ping Lu and Ping Gong,”Global 4-D trajectory optimization for spacecraft”,Science China Technological Sciences,2010,Vol.53(8),pp.2097-2101.
[9]John T.Betts,”Survey of Numerical Methods for Trajectory Optimization[J]”,Journal of Guidance,Control,and Dynamics,1998,21(2):193-207.
[10]David G.Hull,”Conversion of optimal control problems into parameter optimization problems[J]”,Journal of Guidance,Control,and Dynamics.1997,20(1):57-60.
[11]Brian C.Fabien,”Some tools for the direct solution of optimal control problems[J]”,Advances in Engineering Software,1998,29(1):45-61.
[12]David Marcelo Garza,”Application of automatic differentiation to trajectory optimization via direct multiple shooting[D]”,Austin,Texas:The University of Texas at Austin,2003.
[13]Gang Chen,Ying Hu,Ziming Wan,Min Xu and Shilu Chen,”Optimization design on RLV reentry trajectory based on genetic algorithm”,Journal of Solid Rocket Technology,2006,29(4):235-238.
[14]Dingni Zhang and Yi Liu,”Reentry trajectory optimization based on proved genetic algorithm and sequential quadratic programming[J]”,Aerospace Control,2009,27(6):8-13.
[15]Qingzhen Zhang,Zhenbo Wang,Fei Tao,Bhaba R.Sarker,Lin Cheng and Shantung Tu,”Design of Optimal Attack-Angle for RLV Reentry Based on Quantum Particle Swarm Optimization”,Advances in Mechanical Engineering,2014,Vol.2014.
[16]Jiang Zhao,Rui Zhou and Xuelian Jin,”Progress in reentry trajectory planning for hypersonic vehicle[J]”,Journal of Systems Engineering and Electronics,2014,25(4):627-639.
[17]Gonzalo Joya,Miguel Atencia and Francisco Sandoval,”Hopfield neural networks for optimization:study of the different dynamics”,Neurocomputing.2002,43(1-4):219-237.
[18]Miguel Atencia and Gonzalo Joya,”Hopfield networks:from optimization to adaptive control”,International Joint Conference on Neural Networks,2015.
[19]Bin Zhang,Shiyi Guan and Shilu Chen,”Modified ant colony algorithm-based reentry trajectory optimization for suborbital launch vehicle[J]”,Journal of Astronautics,2011,32(6):1244-1248.
[20]Zachary J Kiyak,Roy J Hartfield and Timothy W Ledlow,”Missile trajectory optimization using a modified ant colony algorithm”,Proc.of the Aerospace Conference,2014:1-8.
[21]Shouwei Gao,Yeqing Yang and Weidong Zhang,”Trajectory Planning for Cruise Missile in Three-Dimensional Space Based on Improved Ant Colony Algorithm”,Journal of Shanghai Jiaotong University,2010.
[22]Runqi Chai,”Violation learning deferential evolution-based hp-adaptive pseudospectral method for trajectory optimization of Space Maneuver Vehicle”,IEEE,2016.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |