期刊文献+

基于MOEA/D的柔性结构燃料—时间多目标优化控制研究 被引量:3

Fuel-time Multiobjective Optimal Control of Flexible Structures Based on MOEA/D
下载PDF
导出
摘要 利用基于分解的多目标优化算法(MOEA/D)研究了柔性航天器多目标优化的rest-to-rest机动问题。基于空间飞行器刚柔耦合动力学方程,提出了最小时间—最少耗能的多目标优化控制模型;给出了基于MOEA/D的算法框架,并对柔性飞行器空间机动问题进行了多目标优化控制的分析设计;典型算例表明该算法可有效地应用于柔性航天器姿态机动控制器的分析设计之中。 A multi-objective optimization for rest-to-rest maneuvers of flexible spacecraft is presented by using MOEA/D (Multiobjective Evolutionary Algorithm based on Decomposition). The multiobjective control design functions which deal with the minimal maneuver time and fuel consume are developed by using rigid-flexible couple dynamics model of spacecraft. A new MOEA/D approach is introduced for maneuvers problem of flexible spacecraft control system. The simulation results show that the approach can be efficiently realized in design and analysis of flexible spaeecraft.
出处 《国防科技大学学报》 EI CAS CSCD 北大核心 2009年第6期73-76,105,共5页 Journal of National University of Defense Technology
基金 国防科技大学预研基金国际合作资助项目(GJ07-01-01)
关键词 多目标优化 柔性航天器 姿态机动 multiobjective optimization flexible spacecraft attitude maneuvers
  • 相关文献

参考文献8

  • 1Singh G, Kabamba P T, McClamroch N H. Planar Time-optimal Control, Rest-to-rest Slewing of Flexible Spacecraft [ J ]. AIAA Journal of Guidance, Control and Dynamics, 1989, 12(1): 71-81.
  • 2Wie B, Sinha R, Sunkel J, et al. Robust Fuel and Time-optimal Control of Uncertain Flexible Space Structures[C]//AIAA Guidance, Navigation and Control Conference, 1993:939 - 948.
  • 3Hartmann R, Singh T. Fuel/Time Optimal Control of Flexible Space Structures[C]//AIAA Guidance, Navigation and Control Conference, 1995:91 - 101.
  • 4Sunar M, Kahraman R. A Comparative Study of Multiobjective Optimization Methods in Structural Edsign[J]. Turk. J. Engin. Environ. Sci., 2001(25): 69-78.
  • 5Mainenti I, DeSouza L C G, Sousa F L D, et al. Satellite Attitude Control Using the Generalized Extremal Optimization with a Multi-objective Approach[C]//Proceedings of COBEM,2007.
  • 6黄敏,陈国龙,郭文忠.基于表现型共享的多目标粒子群算法研究[J].福州大学学报(自然科学版),2007,35(3):365-369. 被引量:5
  • 7Zhang Q, Li H. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposidon[J]. 1EEE Transactions on Evolutionary, Computation, 2006.
  • 8Singh T. Fuel/Time Optimal Control of the Benchmark Problem[J]. Journal of Guidance, Control, and Dynamics, 1995, 18(6) : 1225 - 1230.

二级参考文献8

  • 1Srinivas N,Deb K.Multiobjective optimization using nondominated sorting in genetic algorithms[J].Evolutionary Computation,1994,2(3):221-248.
  • 2Deb K,Agrawal S,Pratap A,et al.A fast elitist non-dominated sorting genetic algorithm for multi-objective optimisation:NSGA-Ⅱ[C]//Proceeding of the Parallel Problem Solving from Nature Ⅵ Conference.[s.l.]:Springer,2000:849 -858.
  • 3Zitzler E,Laumanns M,Thiele L.SPEA2:improving the strength pareto evolutionary algorithm[R].Technical Report 103.Zurich:Computer Engineering and Networks Laboratory of ETH,2001.
  • 4Kennedy J,Eberhart R C.Particle swarm optimization[C]//Proceedings of IEEE International Conference on Neural Networks.Piscataway:IEEE,1995:1942-1948.
  • 5Chen G,Guo W,Tu X,et al.An improved genetic algorithm for multi -objective optimization[C]//ISICA2005:Progress in Intelligent Computation and Its Applications.Wuhan:China University of Geosciences Press,2005:204-210.
  • 6Zitzler E.Evolutionary algorithms for multiobjective optimization:methods and applications[D].Zurich:Swiss Federal Institute of Technology (ETH),1999.
  • 7Knowles J D,Thiele L,Zitzler E.A tutorial on the performance assessment of stochastic multiobjective optimizers[R].TIKReport No.214.Revised Version.Zurich:Computer Engineering and Networks Laboratory of ETH,2006.
  • 8Conover W J.Practical nonparametric statistics[M].3rd ed.[s.l.]:Wiley,1999.

共引文献4

同被引文献38

  • 1Vaclav Dvorak,Pavel Safarik.Transonic Instability in Entrance Part of Mixing Chamber of High-Speed Ejector[J].Journal of Thermal Science,2005,14(3):258-263. 被引量:5
  • 2荣伟.火星探测器减速着陆技术研究[D].中国空间技术研究院,2008.
  • 3赵汉元.飞行器再人动力学和制导[M].长沙:国防科技大学出版社.1997.
  • 4Theisinger J E, Braun R D. Multi-objective hypersonic entry aeroshell shape optimization[J]. Journal of Space- craft and Rockets, 2009, 46(5): 957-966.
  • 5Johnson J E. Aerothermodynamie optimization of Earth entry blunt-body heat shields for lunar and Mars return [D]. Washington, D, C. : University of Maryland, 2009.
  • 6Johnson J E, Starkey R P, Lewis M J. Aerothermody- namie optimization of reentry heat shield shapes for a crew exploration vehicle[J]. Journal of Spacecraft and Rockets, 2007, 44(4) : 849-859.
  • 7Grant M J, Mendeck G F. Mars science laboratory entry optimization using particle swarm methodology [C]ffAIAA Atmospheric Flight Meehanies Confereneeand Exhibit, 2007.
  • 8Deb K, Pratap A, Agrwal S, et al. A fast and elitist mul- tiobjective genetic algorithm: NSGA-II[J]. IEEE Trans- actions on Evolutionary Computation, 2002, 6(2) : 182-197.
  • 9Zhang Q, Li H. MOEA/D: a multiobjective evolutionary algorithm based on decomposition[J]. IEEE Transactions on Evolutionary Computation, 2007, 11(6): 712-731.
  • 10Konstantinidis A, Yang K. Multi-objective energy-effi- cient dense deployment in wireless sensor networks using a hybrid problem-specific MOEA/D[J]. Applied Soft Com- puting, 2011, 11(6): 4117-4134.

引证文献3

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部