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Discrete control of longitudinal dynamics for hypersonic flight vehicle using neural networks

基于神经网络的高超声速飞行器纵向离散控制

  • Research Paper
  • Special Focus on Advanced Nonlinear Control of Hypersonic Flight Vehicles
  • Published:
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Abstract

The discrete controller is developed for the longitudinal dynamics of the hypersonic flight vehiclewith neural networks (NNs). The focus is on the control of the Euler equations of attitude dynamics. Withback-stepping design, for each step the virtual control is constructed with NNs approximating the unknowndynamics. The design uses less online adaption parameter learning scheme to achieve the control goal. It isguaranteed that the errors of all the signals in the system are uniformly ultimately bounded. The proposedmethod is verified by simulation of winged-cone model.

创新点

本文针对高超声速飞行器的纵向通道模型, 建立了一种离散控制方法。围绕姿态动力学的欧拉方程采用反步法策略进行控制器设计, 在每一步都设计了一个虚拟控制量。针对模型中存在的未知动力学, 通过神经网络来逼近。与已有的研究不同, 本文的创新点在于利用最小在线参数学习策略实现离散控制器的设计, 并通过李雅普诺夫方法证明了所建立的控制器可保证闭环系统信号是一致终值有界的。最后通过winged-cone模型进行了仿真, 验证了所建立算法的有效性。

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References

  1. Raptis I A, Valavanis K P, Moreno W A. System identification and discrete nonlinear control of miniature helicoptersusing backstepping. J Intell Robot Syst, 2009, 55: 223–243

    Article  MATH  Google Scholar 

  2. Corradini M, Orlando G. Control of mobile robots with uncertainties in the dynamical model: a discrete time slidingmode approach with experimental results. Control Eng Pract, 2002, 10: 23–34

    Article  Google Scholar 

  3. Sun F, Li H, Li L. Robot discrete adaptive control based on dynamic inversion using dynamical neural networks.Automatica, 2002, 38: 1977–1983

    Article  MATH  Google Scholar 

  4. Stengel R, Broussard J, Berry P. Digital controllers for vtol aircraft. IEEE Trans Aerosp Electron Syst, 1978, 14:54–63

    Google Scholar 

  5. Xu B, Yang C, Shi Z K. Reinforcement learning output feedback NN control using deterministic learning technique. IEEE Trans Neural Netw Learn Syst, 2014, 25: 635–641

    Article  Google Scholar 

  6. Liu Y J, Chen C L P, Wen G X, et al. Adaptive neural output feedback tracking control for a class of uncertaindiscrete-time nonlinear systems. IEEE Trans Neural Netw, 2011, 22: 1162–1167

    Article  Google Scholar 

  7. Shin D, Kim Y. Nonlinear discrete-time reconfigurable flight control law using neural networks. IEEE Trans ControlSyst Technol, 2006, 14: 408–422

    Article  Google Scholar 

  8. Xu B, Wang D, Wang H, et al. Adaptive neural control of a hypersonic vehicle in discrete time. J Intell Robot Syst,2014, 73: 219–231

    Article  Google Scholar 

  9. Buschek H, Calise A J. Uncertainty modeling and fixed-order controller design for a hypersonic vehicle model. J GuidControl Dynam, 1997, 20: 42–48

    Article  Google Scholar 

  10. Marrison C I, Stengel R F. Design of robust control systems for a hypersonic aircraft. J Guid Control Dynam, 1998,21: 58–63

    Google Scholar 

  11. Xu B, Gao D, Wang S. Adaptive neural control based on HGO for hypersonic flight vehicles. Sci China Inf Sci, 2011,54: 511–520

    Google Scholar 

  12. Wang Q, Stengel R. Robust nonlinear control of a hypersonic aircraft. J Guid Control Dynam, 2000, 23: 577–585

    Article  Google Scholar 

  13. Gao D, Sun Z. Fuzzy tracking control design for hypersonic vehicles via T-S model. Sci China Inf Sci, 2011, 54:521–528

    Google Scholar 

  14. Xu B, Huang X, Wang D, et al. Dynamic surface control of constrained hypersonic flight models with parameterestimation and actuator compensation. Asian J Control, 2014, 16: 162–174

    Article  MATH  MathSciNet  Google Scholar 

  15. Rehman O, Fidan B, Petersen R. Uncertainty modeling and robust minimax LQR control of multivariable nonlinearsystems with application to hypersonic flight. Asian J Control, 2012, 14: 1180–1193

    Article  MATH  MathSciNet  Google Scholar 

  16. Hu X, Gao H, Karimi H R, et al. Fuzzy reliable tracking control for flexible air-breathing hypersonic vehicles. Int JFuzzy Syst, 2011, 13: 323–333

    MathSciNet  Google Scholar 

  17. Gibson T, Crespo L, Annaswamy A. Adaptive control of hypersonic vehicles in the presence of modeling uncertainties.In: Proceedings of American Control Conference. New York: IEEE Press, 2009. 3178–3183

    Book  Google Scholar 

  18. Xu H, Mirmirani M, Ioannou P. Adaptive sliding mode control design for a hypersonic flight vehicle. J Guid ControlDynam, 2004, 27: 829–838

    Article  Google Scholar 

  19. Fiorentini L, Serrani A, Bolender M, et al. Nonlinear robust adaptive control of flexible air-breathing hypersonicvehicles. J Guid Control Dynam, 2009, 32: 401–416

    Article  Google Scholar 

  20. Xu B, Shi Z K. An overview on flight dynamics and control approaches for hypersonic vehicles. Sci China Inf Sci,2015, 58: 070201

  21. Xu B, Sun F, Yang C, et al. Adaptive discrete-time controller design with neural network for hypersonic flight vehiclevia back-stepping. Int J Control, 2011, 84: 1543–1552

    Article  MATH  MathSciNet  Google Scholar 

  22. Xu B, Sun F, Liu H, et al. Adaptive kriging controller design for hypersonic flight vehicle via back-stepping. IETControl Theory Appl, 2012, 6: 487–497

    Article  MathSciNet  Google Scholar 

  23. Li T S, Wang D, Feng G, et al. A DSC approach to robust adaptive NN tracking control for strict-feedback nonlinearsystems. IEEE Trans Syst Man Cybern Part B-Cybern, 2010, 40: 915–927

    Article  Google Scholar 

  24. Xu B, Pan Y,Wang D, et al. Discrete-time hypersonic flight control based on extreme learning machine. Neurocomput,2014, 128: 232–241

    Article  Google Scholar 

  25. Xu B, Wang D, Sun F, et al. Direct neural discrete control of hypersonic flight vehicle. Nonlinear Dyn, 2012, 70:269–278

    Article  MATH  MathSciNet  Google Scholar 

  26. Ge S, Hang C, Lee T, et al. Stable Adaptive Neural Network Control. Norwell: Kluwer Academic, 2001

  27. Pan Y, Zhou Y, Sun T, et al. Composite adaptive fuzzy H8 tracking control of uncertain nonlinear systems. Neurocomput,2013, 99: 15–24

    Article  Google Scholar 

  28. Xu B, Shi Z K, Yang C, et al. Composite neural dynamic surface control of a class of uncertain nonlinear systems instrict-feedback form. IEEE Trans Cybern, 2014, 14: 2626–2634

    Article  Google Scholar 

  29. Xu B, Shi Z K, Yang C G. Composite fuzzy cntrol of a class of uncertain nonlinear systems with disturbance observer.Nonlinear Dyn, 2015, 80: 341–351

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. School of Automation, Northwestern Polytechnical University, Xi’an, 710072, China

    YongFeng Zhi & YunYi Yang

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  1. YongFeng Zhi
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  2. YunYi Yang
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Correspondence to YongFeng Zhi.

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Zhi, Y., Yang, Y. Discrete control of longitudinal dynamics for hypersonic flight vehicle using neural networks. Sci. China Inf. Sci. 58, 1–10 (2015). https://doi.org/10.1007/s11432-015-5351-5

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  • DOI: https://doi.org/10.1007/s11432-015-5351-5

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