Science China Information Sciences

, Volume 58, Issue 7, pp 1–19 | Cite as

An overview on flight dynamics and control approaches for hypersonic vehicles

  • Bin XuEmail author
  • ZhongKe Shi
Review Special Focus on Advanced Nonlinear Control of Hypersonic Flight Vehicles


With the capability of high speed flying, a more reliable and cost efficient way to access space isprovided by hypersonic flight vehicles. Controller design, as key technology to make hypersonic flight feasibleand efficient, has numerous challenges stemming from large flight envelope with extreme range of operationconditions, strong interactions between elastic airframe, the propulsion system and the structural dynamics.This paper briefly presents several commonly studied hypersonic flight dynamics such as winged-cone model,truth model, curve-fitted model, control oriented model and re-entry motion. In view of different schemes such aslinearizing at the trim state, input-output linearization, characteristic modeling, and back-stepping, the recentresearch on hypersonic flight control is reviewed and the comparison is presented. To show the challenges forhypersonic flight control, some specific characteristics of hypersonic flight are discussed and the potential futureresearch is addressed with dealing with actuator dynamics, aerodynamic/reaction-jet control, flexible effects,non-minimum phase problem and dynamics interaction.


hypersonic flight vehicle linearizing at the trim state input-output linearization back-stepping non-minimum phase 



高超声速飞行器具有突出的飞行能力, 可为进入太空提供更加可靠和有效的途径; 作为高超声速技术重要方面之一的控制技术面临诸多挑战。本文首先给出锥体加速器模型、真实模型、曲线拟合模型、面向控制的模型以及再入运动等常用于研究的高超声速飞行器模型。其次, 分别根据小扰动线性化、输入输出线性化、特征建模、反步法等不同处理非线性动力学策略出发, 对高超声速飞行器相关控制研究进行总结和对比分析。最后, 结合高超声速飞行器的特殊飞行环境和动力学特点, 提供了未来可供研究的方向, 包括重点解决大包络快速自适应设计、气动力/直接力复合控制、气动弹性颤振控制、静不稳定控制等问题。


高超声速飞行器 小扰动线性化 输入输出线性化 反步法 非最小相位 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

11432_2014_5273_MOESM1_ESM.pdf (44 kb)
Supplementary material, approximately 45 KB.


  1. 1.
    Fidan B, Mirmirani M, Ioannou P. Flight dynamics and control of air-breathing hypersonic vehicles: Review and newdirections. In: AIAA International Space Planes and Hypersonic Systems and Technologies, Virginia, 2003. 2003–7081Google Scholar
  2. 2.
    Wu H, Meng B. Review on the control of hypersonic flight vehicles. Adv Mech, 2009, 39: 756–765Google Scholar
  3. 3.
    Duan H, Li P. Progress in control approaches for hypersonic vehicle. Sci China Tech Sci, 2012, 55: 2965–2970CrossRefGoogle Scholar
  4. 4.
    Ataei A, Wang Q. Nonlinear control of an uncertain hypersonic aircraft model using robust sum-of-squares method. IET Contr Theor Appl, 2012, 6: 203–215MathSciNetCrossRefGoogle Scholar
  5. 5.
    Xu H, Mirmirani M, Ioannou P. Adaptive sliding mode control design for a hypersonic flight vehicle. J Guid ContrDyn, 2004, 27: 829–838CrossRefGoogle Scholar
  6. 6.
    Gao D, Sun Z, Du T. Dynamic surface control for hypersonic aircraft using fuzzy logic system. In: IEEE InternationalConference on Automation and Logistics, Jinan, 2007. 2314–2319Google Scholar
  7. 7.
    Sun Y, Hou M, Duan G, et al. On-line optimal autonomous reentry guidance based on improved gauss pseudospectralmethod. Sci China Inf Sci, 2014, 57: 052203Google Scholar
  8. 8.
    Xu B, Huang X, Wang D, et al. Dynamic surface control of constrained hypersonic flight models with parameterestimation and actuator compensation. Asian J Contr, 2014, 16: 162–174zbMATHMathSciNetCrossRefGoogle Scholar
  9. 9.
    Wilcox Z, MacKunis W, Bhat S, et al. Robust nonlinear control of a hypersonic aircraft in the presence of aerothermoelasticeffects. In: IEEE American Control Conference, St. Louis, 2009. 2533–2538Google Scholar
  10. 10.
    Jiang B, Gao Z, Shi P, et al. Adaptive fault-tolerant tracking control of near-space vehicle using takagi–sugeno fuzzymodels. IEEE Trans Fuzzy Syst, 2010, 18: 1000–1007CrossRefGoogle Scholar
  11. 11.
    Shaughnessy J, Pinckney S, Mcminn J, et al. Hypersonic vehicle simulation model: Winged-cone configuration. NASATM-102610, 1990Google Scholar
  12. 12.
    Bolender M, Doman D. Nonlinear longitudinal dynamical model of an air-breathing hypersonic vehicle. J SpacecraftRockets, 2007, 44: 374–387CrossRefGoogle Scholar
  13. 13.
    Parker J, Serrani A, Yurkovich S, et al. Control-oriented modeling of an air-breathing hypersonic vehicle. J GuidContr Dyn, 2007, 30: 856–869Google Scholar
  14. 14.
    Li H, Lin P, Xu D. Control-oriented modeling for air-breathing hypersonic vehicle using parameterized configuration approach. Chin J Aeronaut, 2011, 24: 81–89CrossRefGoogle Scholar
  15. 15.
    Buschek H, Calise A. Uncertainty modeling and fixed-order controller design for a hypersonic vehicle model. J GuidContr Dyn, 1997, 20: 42–48Google Scholar
  16. 16.
    Dydek Z, Annaswamy A, Lavretsky E. Adaptive control and the NASA x-15-3 flight revisited. IEEE Contr Syst Magaz, 2010, 30,: 32–48MathSciNetCrossRefGoogle Scholar
  17. 17.
    Gibson T, Crespo L, Annaswamy A. Adaptive control of hypersonic vehicles in the presence of modeling uncertainties.In: IEEE American Control Conference, St. Louis 2009. 3178–3183Google Scholar
  18. 18.
    Zerar M, Cazaurang F, Zolghadri A. Coupled linear parameter varying and flatness-based approach for space re-entryvehicles guidance. IET Contr Theor Appl, 2009, 3: 1081–1092MathSciNetCrossRefGoogle Scholar
  19. 19.
    Hu X, Wu L, Hu C, et al. Adaptive sliding mode tracking control for a flexible air-breathing hypersonic vehicle. JFranklin Inst, 2012, 349: 559–577zbMATHMathSciNetCrossRefGoogle Scholar
  20. 20.
    Marrison C, Stengel F. Design of robust control systems for a hypersonic aircraft. J Guid Contr Dyn, 1998, 21: 58–63zbMATHCrossRefGoogle Scholar
  21. 21.
    Wang Q, Stengel R. Robust nonlinear control of a hypersonic aircraft. J Guid Contr Dyn, 2000, 23: 577–585CrossRefGoogle Scholar
  22. 22.
    Kokotovic P. The joy of feedback: nonlinear and adaptive: 1991 Bode Prize Lecture. IEEE Contr Syst Magaz, 1991, 12: 7–17CrossRefGoogle Scholar
  23. 23.
    Xu B, Shi Z, Yang C, et al. Composite neural dynamic surface control of a class of uncertain nonlinear systems instrict-feedback form. IEEE Trans Cybern, 2014, 14: 2626–2634CrossRefGoogle Scholar
  24. 24.
    Gong Y, Wu H. Characteristic model-based adaptive attitude control for hypersonic vehicle. J Astron, 2010, 31:2122–2128Google Scholar
  25. 25.
    Hu Y, Yuan Y, Min H, et al. Multi-objective robust control based on fuzzy singularly perturbed models for hypersonicvehicles. Sci China Inf Sci, 2011, 54: 563–576zbMATHMathSciNetCrossRefGoogle Scholar
  26. 26.
    Janardhanan S, Bandyopadhyay B. Multirate output feedback based robust quasi-sliding mode control of discrete-timesystems. IEEE Trans Autom Contr, 2007, 52: 499–503MathSciNetCrossRefGoogle Scholar
  27. 27.
    Xu B, Sun F, Liu H, et al. Adaptive kriging controller design for hypersonic flight vehicle via back-stepping. IETContr Theor Appl, 2012, 6: 487–497MathSciNetCrossRefGoogle Scholar
  28. 28.
    Xu B, Shi Z, Yang C, et al. Neural control of hypersonic flight vehicle model via time-scale decomposition with throttlesetting constraint. Nonlinear Dyn, 2013, 73: 1849–1861zbMATHMathSciNetCrossRefGoogle Scholar
  29. 29.
    Chavez R, Schmidt K. Analytical aeropropulsive-aeroelastic hypersonic-vehicle model with dynamic analysis. J GuidContr Dyn, 1994, 17: 1308–1319zbMATHGoogle Scholar
  30. 30.
    Fiorentini L, Serrani A, Bolender M, et al. Nonlinear robust adaptive control of flexible air-breathing hypersonicvehicles. J Guid Contr Dyn, 2009, 32: 401–416CrossRefGoogle Scholar
  31. 31.
    Bolender M, Doman D. A non-linear model for the longitudinal dynamics of a hypersonic air-breathing vehicle. In:AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco 2005. 6255CrossRefGoogle Scholar
  32. 32.
    Groves P, Sigthorsson O, Serrani A, et al. Reference command tracking for a linearized model of an air-breathinghypersonic vechicle. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco 2005. AIAA2005a–6144Google Scholar
  33. 33.
    Sigthorsson O, Sarrani A. Development of linear parameter-varying models of hypersonic air-breathing vehicles. In:AIAA Guidance, Navigation, and Control Conference, Chicago, 2009. AIAA 2009-6282CrossRefGoogle Scholar
  34. 34.
    Shtessel Y, McDuffie J, Jackson M. Sliding mode control of the X-33 vehicle in launch and re-entry modes. In: AIAAGuidance, Navigation and Control Conference, Boston, 1998. AIAA-98-4414CrossRefGoogle Scholar
  35. 35.
    Schmidt K. Optimum mission performance and multivariable flight guidance for airbreathing launch vehicles. J GuidContr Dyn, 1997, 20: 1157–1164zbMATHGoogle Scholar
  36. 36.
    Chavez R, Schmidt K. Uncertainty modeling for multivariable-control robustness analysis of elastic high-speed vehicles. J Guid Contr Dyn, 1999, 22: 87–95CrossRefGoogle Scholar
  37. 37.
    Sigthorsson D, Jankovsky P, Serrani A, et al. Robust linear output feedback control of an airbreathing hypersonicvehicle. J Guid Contr Dyn, 2008, 31: 1052–1066CrossRefGoogle Scholar
  38. 38.
    Hu Y, Sun F, Liu H. Neural network-based robust control for hypersonic flight vehicle with uncertainty modelling. Intern J Mod Identif Contr, 2010, 11: 87–98CrossRefGoogle Scholar
  39. 39.
    Chen M, Jiang C,Wu Q. Disturbance-observer-based robust flight control for hypersonic vehicles using neural networks. Adv Sci Lett, 2011, 4: 4–5Google Scholar
  40. 40.
    Li H, Wu L, Gao H, et al. Reference output tracking control for a flexible air-breathing hypersonic vehicle via outputfeedback. Opt Contr Appl Methods, 2012, 33: 461–487zbMATHMathSciNetCrossRefGoogle Scholar
  41. 41.
    Li H, Si Y, Wu L, et al. Guaranteed cost control with poles assignment for a flexible air-breathing hypersonic vehicle. Intern J Syst Sci, 2011, 42: 863–876zbMATHMathSciNetCrossRefGoogle Scholar
  42. 42.
    Mehta S, MacKunisW, Subramanian S, et al. Nonlinear control of hypersonic missiles for maximum target penetration.In: AIAA Guidance, Navigation, and Control Conference, Minneapolis, 2012. AIAA 2012-4886CrossRefGoogle Scholar
  43. 43.
    Li X, Xian B, Diao C, et al. Output feedback control of hypersonic vehicles based on neural network and high gainobserver. Sci China Inf Sci, 2011, 54: 429–447zbMATHMathSciNetCrossRefGoogle Scholar
  44. 44.
    Yang J, Li S, Sun C, et al. Nonlinear-disturbance-observer-based robust flight control for airbreathing hypersonicvehicles. IEEE Trans Aerospace Electr Syst, 2013, 49: 1263–1275CrossRefGoogle Scholar
  45. 45.
    Rehman O, Fidan B, Petersen R. Uncertainty modeling and robust minimax LQR control of multivariable nonlinearsystems with application to hypersonic flight. Asian J Contr, 2012, 14: 1180–1193zbMATHMathSciNetCrossRefGoogle Scholar
  46. 46.
    Sun H, Li S, Sun C. Finite time integral sliding mode control of hypersonic vehicles. Nonlinear Dyn, 2013, 73: 229–244zbMATHCrossRefGoogle Scholar
  47. 47.
    Gao D, Sun Z. Fuzzy tracking control design for hypersonic vehicles via T-S model. Sci China Inf Sci, 2011, 54:521–528zbMATHMathSciNetCrossRefGoogle Scholar
  48. 48.
    Zhang Z, Hu J. Stability analysis of a hypersonic vehicle controlled by the characteristic model based adaptive controller. Sci China Inf Sci, 2012, 55: 2243–2256zbMATHMathSciNetCrossRefGoogle Scholar
  49. 49.
    Hu X, Gao H, Karimi H, et al. Fuzzy reliable tracking control for flexible air-breathing hypersonic vehicles. Intern JFuzzy Syst, 2011, 13: 323–333MathSciNetGoogle Scholar
  50. 50.
    Luo X, Li J. Fuzzy dynamic characteristic model based attitude control of hypersonic vehicle in gliding phase. SciChina Inf Sci, 2011, 54: 448–459zbMATHCrossRefGoogle Scholar
  51. 51.
    Li H, Sun Z, Min H, et al. Fuzzy dynamic characteristic modeling and adaptive control of nonlinear systems and itsapplication to hypersonic vehicles. Sci China Inf Sci, 2011, 54: 460–468zbMATHMathSciNetCrossRefGoogle Scholar
  52. 52.
    Xu B, Wang D, Sun F, et al. Direct neural discrete control of hypersonic flight vehicle. Nonlinear Dyn, 2012, 70:269–278zbMATHMathSciNetCrossRefGoogle Scholar
  53. 53.
    Chen M, Ge S, Ren B. Robust attitude control of helicopters with actuator dynamics using neural networks. IETContr Theor Appl, 2010, 4: 2837–2854MathSciNetCrossRefGoogle Scholar
  54. 54.
    Xu B, Gao D, Wang S. Adaptive neural control based on HGO for hypersonic flight vehicles. Sci China Inf Sci, 2011,54: 511–520zbMATHMathSciNetCrossRefGoogle Scholar
  55. 55.
    Yang C, Ge S, Xiang C, et al. Output feedback NN control for two classes of discrete-time systems with unknowncontrol directions in a unified approach. IEEE Trans Neural Networks, 2008, 19: 1873–1886CrossRefGoogle Scholar
  56. 56.
    Liu Y, Tong S, Chen P. Adaptive fuzzy control via observer design for uncertain nonlinear systems with unmodeleddynamics. IEEE Trans Fuzzy Syst, 2013, 21: 275–288CrossRefGoogle Scholar
  57. 57.
    Chen W, Jiao L, Li J, et al. Adaptive NN backstepping output-feedback control for stochastic nonlinear strict-feedbacksystems with time-varying delays. IEEE Trans Syst Man Cybern-Part B: Cybernet, 2010, 40: 939-950Google Scholar
  58. 58.
    Gao D, Sun Z, Luo X, et al. Fuzzy adaptive control for hypersonic vehicle via backstepping method. Contr TheorAppl, 2008, 25: 805–810Google Scholar
  59. 59.
    Xu B, Wang S, Gao D, et al. Command filter based robust nonlinear control of hypersonic aircraft with magnitudeconstraints on states and actuators. J Intell Robotic Syst, 2014, 73: 233–247CrossRefGoogle Scholar
  60. 60.
    Chen M, Jiang B. Robust attitude control of near space vehicles with time-varying disturbances. Intern J Contr AutomSyst, 2013, 11: 182–187MathSciNetCrossRefGoogle Scholar
  61. 61.
    Chen M, Wu Q, Jiang C. Disturbance-observer-based robust synchronization control of uncertain chaotic systems. Nonlinear Dyn, 2012, 70: 2421–2432MathSciNetCrossRefGoogle Scholar
  62. 62.
    Chen M, Wu Q, Jiang C, et al. Guaranteed transient performance based control with input saturation for near spacevehicles. Sci China Inf Sci, 2014, 57: 1–12MathSciNetGoogle Scholar
  63. 63.
    Fiorentini L, Serrani A, Bolender M, et al. Robust nonlinear sequential loop closure control design for an air-breathinghypersonic vehicle model. In: IEEE American Control Conference, Seattle, 2008. 3458–3463Google Scholar
  64. 64.
    Xu B. Robust adaptive neural control of flexible hypersonic flight vehicle with dead-zone input nonlinearity. Nonlinear Dynamics, doi: 10.1007/s11071-015-1958-8Google Scholar
  65. 65.
    Fiorentini L, Serrani A. Adaptive restricted trajectory tracking for a non-minimum phase hypersonic vehicle model. Automatica, 2012, 48: 1248–1261zbMATHMathSciNetCrossRefGoogle Scholar
  66. 66.
    Sun H, Yang Z, Zeng J. New tracking-control strategy for airbreathing hypersonic vehicles. J Guid Contr Dyn, 2013,36: 846–859zbMATHCrossRefGoogle Scholar
  67. 67.
    Butt W, Yan L, Kendrick A. Adaptive dynamic surface control of a hypersonic flight vehicle with improved tracking. Asian J Contr, 2013, 15: 594–605MathSciNetCrossRefGoogle Scholar
  68. 68.
    Zong Q, Ji Y, Zeng F, et al. Output feedback back-stepping control for a generic hypersonic vehicle via small-gaintheorem. Aerospace Sci Tech, 2012, 23: 409–417CrossRefGoogle Scholar
  69. 69.
    Wang Y, Jiang C,Wu Q. Attitude tracking control for variable structure near space vehicles based on switched nonlinearsystems. Chin J Aeronautics, 2013, 26: 186-193Google Scholar
  70. 70.
    Stengel R, Broussard J, Berry P. Digital controllers for vtol aircraft. IEEE Trans Aerospace Electr Syst, 1978, 1: 54–63CrossRefGoogle Scholar
  71. 71.
    Shin D, Kim Y. Nonlinear discrete-time reconfigurable flight control law using neural networks. IEEE Trans ContrSyst Tech, 2006, 14: 408–422CrossRefGoogle Scholar
  72. 72.
    Powly A, Bhat M. Missile autopilot design using discrete-time variable structure controller with sliding sector. J GuidContr Dyn, 2004, 27: 634–646Google Scholar
  73. 73.
    Chaudhuri A, Bhat S. Output feedback-based discrete-time sliding-mode controller design for model aircraft. J GuidContr Dyn, 2005, 28: 177–181Google Scholar
  74. 74.
    Xu B, Sun F, Yang C, et al. Adaptive discrete-time controller design with neural network for hypersonic flight vehiclevia back-stepping. Intern J Contr, 2011, 84: 1543–1552zbMATHMathSciNetCrossRefGoogle Scholar
  75. 75.
    Xu B, Wang D, Wang H, et al. Adaptive neural control of a hypersonic vehicle in discrete time. J Intell Robotic Syst,2014, 73: 219–231CrossRefGoogle Scholar
  76. 76.
    Xu B, Zhang Y. Neural discrete back-stepping control of hypersonic flight vehicle with equivalent prediction model. Neurocomputing, doi: 10.1016/j.neucom.2014.11.059Google Scholar
  77. 77.
    Xu B, Pan Y, Wang D, et al. Discrete-time hypersonic flight control based on extreme learning machine. Neurocomputing,2014, 128: 232–241CrossRefGoogle Scholar
  78. 78.
    Xu B, Wang D, Sun F, et al. Direct neural control of hypersonic flight vehicles with prediction model in discrete time. Neurocomputing, 2013, 115: 39–48CrossRefGoogle Scholar
  79. 79.
    Xu B, Shi Z. Universal kriging control of hypersonic aircraft model using predictor model without back-stepping. IETContr Theor Appl, 2013, 7: 573–583MathSciNetCrossRefGoogle Scholar
  80. 80.
    Wang N, Er M, Han M. Generalized single-hidden layer feedforward networks for regression problems. IEEE TransNeural Networks Learning Syst, doi: 10.1109/TNNLS.2014.2334366Google Scholar
  81. 81.
    Wilcox Z, MacKunis W, Bhat S, et al. Lyapunov-based exponential tracking control of a hypersonic aircraft withaerothermoelastic effects. J Guid Contr Dyn, 2010, 33: 1213–1224CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.School of AutomationNorthwestern Polytechnical UniversityXi’anChina
  2. 2.National Key Laboratory of Aerospace Flight DynamicsNorthwestern Polytechnical UniversityXi’anChina

Personalised recommendations