logo

SCIENTIA SINICA Informationis, Volume 49, Issue 6: 760(2019) https://doi.org/10.1360/N112017-00202

${\mathcal{L}}_{1}$ adaptive control augmentation for a six-degree-of-freedom hypersonic vehicle model

More info
  • ReceivedOct 18, 2017
  • AcceptedMar 13, 2018
  • PublishedJun 6, 2019

Abstract

In this paper, we present the design of an ${\mathcal{L}}_{1}$ adaptive control augmentation system for a six-degree-of-freedom generic hypersonic vehicle model. We focus on addressing system uncertainties, which lead to undesired performance if not properly addressed in the control design. The design begins with the development of a nonlinear dynamic inversion system as the inner-loop controller, which achieves linearization between system inputs and outputs. Linear feedback controllers are then designed as a baseline control system. In addition, the ${\mathcal{L}}_{1}$ adaptive control architecture is used to develop augmentation setups to enhance the control performance of the baseline controllers in the presence of system uncertainties and disturbances. The simulation results demonstrate that the proposed augmentation scheme improves the overall control performance and enhances the robustness of the control system.


Supplement

补充材料包括以下内容: (1) 高超音速飞行器动力学模型主要变量及参数表; (2) 仿真试验情形III, V及VI中的跟踪误差曲线及控制输入图线; (3) 试验情形I中高超音速飞行器的三维运动轨迹; (4) 各仿真试验中控制方案性能指标的比较.


References

[1] Hallion R. The history of hypersonics: or, `back to the future: again and again'. In: Proceedings of the 43rd AIAA Aerospace Sciences Meeting and Exhibit, Reno, 2005. Google Scholar

[2] Tang M, Chase R. The quest for hypersonic flight with air-breathing propulsion. In: Proceedings of the 15th AIAA International Space Planes and Hypersonic Systems and Technologies Conference, Dayton, 2008. Google Scholar

[3] Echols J A, Puttannaiah K, Mondal K, et al. Fundamental control system design issues for scramjet-powered hypersonic vehicles. In: Proceedings of AIAA Guidance, Navigation, and Control Conference, Kissimmee, 2015. Google Scholar

[4] National Research Council (U.S.). Committee on Hypersonic Technology for Military Application. Hypersonic Technology for Military Application. Washington: National Academy Press, 1989. Google Scholar

[5] Snell S A, Nns D F, Arrard W L. Nonlinear inversion flight control for a supermaneuverable aircraft. J Guid Control Dyn, 1992, 15: 976--984. Google Scholar

[6] Lee H, Reiman S, Dillon C, et al. Robust nonlinear dynamic inversion control for a hypersonic cruise vehicle. In: Proceedings of AIAA Guidance, Navigation and Control Conference and Exhibit, Hilton Head, 2007. Google Scholar

[7] Wang P, Tang G J, Wu J. Sliding mode decoupling control of a generic hypersonic vehicle based on parametric commands. Sci China Inf Sci, 2015, 58: 052202 CrossRef Google Scholar

[8] Xu H J, Mirmirani M D, Ioannou P A. Adaptive sliding mode control design for a hypersonic flight vehicle. J Guid Control Dyn, 2004, 27: 829-838 CrossRef ADS Google Scholar

[9] Pu Z Q, Yuan R Y, Tan X M. Active robust control of uncertainty and flexibility suppression for air-breathing hypersonic vehicles. Aerospace Sci Tech, 2015, 42: 429-441 CrossRef Google Scholar

[10] Fiorentini L, Serrani A, Bolender M A. Nonlinear robust adaptive control of flexible air-breathing hypersonic vehicles. J Guid Control Dyn, 2009, 32: 402-417 CrossRef ADS Google Scholar

[11] Sun H B, Li S H, Sun C Y. Finite time integral sliding mode control of hypersonic vehicles. Nonlinear Dyn, 2013, 73: 229-244 CrossRef Google Scholar

[12] Poderico M, Morani G, Sollazzo A, et al. Fault-tolerant control laws against sensors failures for hypersonic flight. In: Proceedings of the 18th AIAA/3AF International Space Planes and Hypersonic Systems and Technologies Conference, Tours, 2012. Google Scholar

[13] Hellmundt F, Wildschek A, Maier R, et al. Comparison of ${\mathcal{L}}_{1}$ adaptive augmentation strategies for a differential PI baseline controller on a longitudinal F16 aircraft model. In: Advances in Aerospace Guidance, Navigation and Control. Berlin: Springer, 2015. 99--118. Google Scholar

[14] Hovakimyan N, Cao C Y. ${\mathcal{L}}_{1}$ Adaptive Control Theory: Guaranteed Robustness with Fast Adaptation. Philadelphia: Society for Industrial and Applied Mathematics, 2010. Google Scholar

[15] Lei Y, Cao C Y, Cliff E, et al. Design of an ${\mathcal{L}}_{1}$ adaptive controller for air-breathing hypersonic vehicle model in the presence of unmodeled dynamics. In: Proceedings of AIAA Guidance, Navigation and Control Conference and Exhibit, Hilton Head, 2007. Google Scholar

[16] Prime Z, Doolan C, Cazzolato B. Longitudinal ${\mathcal{L}}_{1}$ adaptive control of a hypersonic re-entry experiment. In: Proceedings of the 15th Australian International Aerospace Congress, Melbourne, 2013. 717--726. Google Scholar

[17] Banerjee S, Wang Z, Baur B. L1 adaptive control augmentation for the longitudinal dynamics of a hypersonic glider. J Guid Control Dyn, 2016, 39: 275-291 CrossRef ADS Google Scholar

[18] Heller M, Holzapfel F, Sachs G. Robust lateral control of hypersonic vehicles. In: Proceedings of the 18th Applied Aerodynamics Conference, Denver, 2000. Google Scholar

[19] Mooij E. Adaptive lateral flight control for a winged re-entry vehicle. In: Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit, Austin, 2003. Google Scholar

[20] Daniel P W, Anuradha M A, Jonathan A M, et al. Adaptive control of a generic hypersonic vehicle. In: Proceedings of AIAA Guidance, Navigation, and Control Conference, Boston, 2013. Google Scholar

[21] Banerjee S, Boyce R, Wang Z J. L1 augmented controller for a lateral/directional maneuver of a hypersonic glider. J Aircraft, 2017, 54: 1257-1267 CrossRef Google Scholar

[22] Piao M N, Zhu K, Sun M W, et al. A unified angle control scheme for hypersonic vehicle based on disturbance rejection. In: Proceedings of AIAA International Space Planes and Hypersonics Technologies Conference, Xiamen, 2017. Google Scholar

[23] Colgren R, Keshmiri S, Mirmirani M. Nonlinear ten-degree-of-freedom dynamics model of a generic hypersonic vehicle. J Aircraft, 2009, 46: 800-813 CrossRef Google Scholar

[24] Stevens B L, Lewis F L, Johnson E N. Aircraft Control and Simulation: Dynamics, Controls Design, and Autonomous Systems. Hoboken: John Wiley and Sons, 2016. Google Scholar

[25] Mahmoud M S, Xia Y Q. Applied Control Systems Design. Berlin: Springer, 2012. Google Scholar

[26] Skogestad S, Postlethwaite I. Multivariable Feedback Control: Analysis and Design. Hoboken: John Wiley and Sons, 2005. Google Scholar

  • Figure 1

    Conceptual block diagram of the proposed control scheme

  • Figure 2

    Reference trajectories. (a) $V_r$, (b) $\phi_r$, (c) $\theta_r$, and (d) $\psi_r$

  • Figure 3

    Tracking performance in test case I. (a) $V$, (b) $\phi$, (c) $\theta$, and (d) $\psi$ tracking

  • Figure 4

    Control inputs in test case I. (a) PLA, (b) $\delta_a$, (c) $\delta_e$, and (d) $\delta_r$

  • Figure 5

    Tracking performance in test case II. (a) $V$ and (b) $\phi$ tracking

  • Figure 6

    Tracking performance in test case II. (a) $\theta$ and (b) $\psi$ tracking

  • Figure 7

    Control inputs in test case II. (a) PLA and (b) $\delta_a$

  • Figure 8

    Control inputs in test case II. (a) $\delta_e$ and (b) $\delta_r$

  • Figure 9

    Tracking performance in test case IV. (a) $V$ and (b) $\phi$ tracking

  • Figure 12

    Control inputs in test case IV. (a) $\delta_e$ and (b) $\delta_r$

  • Table 1   Simulation scenarios
    Test case Scenario
    rmI Nominal condition
    rmII Input disturbances
    rmIII Aerodynamic uncertainties
    rmIV Parametric variations
    rmVReduced control functionality
    rmVICombination of the uncertainties of Case II-V
  • Table 2   Bounds of the uncertain aerodynamic coefficients
    Element of error vector Error bounds (3$\sigma$ limits)
    $\epsilon_{C_{L,\alpha}^{\alpha}}$$\left[0.8,1.2\right]$
    $\epsilon_{C_{D,\alpha}^{\alpha}}$$\left[0.83,1.17\right]$
    $\epsilon_{C_{Y,\beta}^M}$ $\left[0.85,1.15\right]$
    $\epsilon_{C_{l,p}^0}$$\left[0.6,1.4\right]$
    $\epsilon_{C_{m,\alpha}^{\alpha}}$ $\left[0.83,1.075\right]$
    $\epsilon_{C_{m,q}^0}$$\left[0.6,1.4\right]$
    $\epsilon_{C_{n,r}^0}$$\left[0.6,1.4\right]$
  • Table 3   Parametric variations
    Parameter Time-varying changes
    $m$$m(t)=(1-\frac{\eta_{\rm~var}}{T_{\rm~sim}}t)m_0$
    $I_{xx}$$I_{xx}(t)=-7.8809\times10^{-5}m^2+25.8857m-6.9683\times10^5$
    $I_{yy}$$I_{yy}(t)=-8.289\times10^{-4}m^2+266m-7.3048\times10^6$
    $I_{zz}$$I_{zz}(t)=I_{yy}(t)$
    $S$$S(t)=\epsilon_{S}S_0$, $\epsilon_{S}\in\left[0.85,1.15\right]$
    $\bar{c}$$\bar{c}(t)=\epsilon_{\bar{c}}\bar{c}_0$, $\epsilon_{\bar{c}}\in\left[0.85,1.15\right]$
    $b$$b(t)=\epsilon_{b}b_{0}$, $\epsilon_{b}\in\left[0.85,1.15\right]$

Copyright 2019 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1