A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 2 Issue 1
Jan.  2015

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 7.847, Top 10% (SCI Q1)
    CiteScore: 13.0, Top 5% (Q1)
    Google Scholar h5-index: 51, TOP 8
Turn off MathJax
Article Contents
Jingmei Zhang, Changyin Sun, Ruimin Zhang and Chengshan Qian, "Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 1, pp. 94-101, 2015.
Citation: Jingmei Zhang, Changyin Sun, Ruimin Zhang and Chengshan Qian, "Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 1, pp. 94-101, 2015.

Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

Funds:

This work was supported by National Outstanding Youth Science Foundation (61125306), National Natural Science Foundation of Major Research Plan (91016004, 61034002), Specialized Research Fund for the Doctoral Program of Higher Education of China (20110092110020), and Open Fund of Key Laboratory of Measurement and Control of Complex Systems of Engineering (Southeast University), Ministry of Education (MCCSE2013B01).

  • Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.

     

  • loading
  • [1]
    He Jie, Zheng De-Zhai. Characteristics and key technology research for hypersonic vehicle. In:Proceedings of the 2012 Aerospace Science and Technology Innovation and the Yangtze River Delta Economic Transformation Development BBS. Lianyungang, China:2012. 227-231(in Chinese)
    [2]
    Chen Zong-Ji, Zhang Ru-Lin, Zhang Ping, Zhou Rui. Flight control, challenges and opportunities. Acta Automatica Sinica, 2013, 39(6):703-710(in Chinese)
    [3]
    Bao Wei-Min. Present situation and development tendency of aerospace control techniques. Acta Automatica Sinica, 2013, 39(6):697-702(in Chinese)
    [4]
    Sun Chang-Yin, Mu Chao-Xu, Yu Yao. Some control problems for near space hypersonic vehicles. Acta Automatica Sinica, 2013, 39(11):1901-1913(in Chinese)
    [5]
    Xu H J, Mirmirani M D, Ioannou P A. Adaptive sliding mode control design for a hypersonic flight vehicle. Journal of Guidance, Control, and Dynamics, 2004, 27(5):829-838
    [6]
    Zhang R M, Sun C Y, Zhang J M, Zhou Y J. Second order terminal sliding mode control for hypersonic vehicle in cruising flight with sliding mode disturbance observer. Journal of Control Theory and Applications, 2013, 11(2):299-305
    [7]
    Zhang R M, Wang L, Zhou Y L. On-line RNN compensated second order nonsingular terminal sliding mode control for hypersonic vehicle. International Journal of Intelligent Computing and Cybernetics, 2012, 5(2):186-205
    [8]
    Li Jing-Jing, Ren Zhang, Song Jian-Shuang. Fuzzy sliding mode control for hypersonic re-entry vehicle. Journal of Shanghai Jiaotong University, 2011, 45(2):295-300(in Chinese)
    [9]
    Da Costa R R, Chu Q P, Mulder J A. Reentry flight controller design using nonlinear dynamic inversion. Journal of Spacecraft and Rockets, 2003, 40(1):64-71
    [10]
    Du Y L, Wu Q X, Jiang C S, Xue Y L. Adaptive recurrent-functionallink- network control for hypersonic vehicles with atmospheric disturbances. Science China, 2011, 54(3):482-497
    [11]
    Wang P, Tang G J, Liu L H, Wu J. Nonlinear hierarchy-structured predictive control design for a generic hypersonic vehicle. Science China Technological Sciences, 2013, 56(8):2015-2036
    [12]
    Kanellakopoulos I, Kokotovic P V, Morse A S. Systematic design of adaptive controllers for feedback linearizable systems. IEEE Transactions on Automatic Control, 1991, 36(11):1241-1253
    [13]
    Koshkouei A J, Zinober A S I. Adaptive backstepping control of nonlinear systems with unmatched uncertainty. In:Proceedings of the 39th IEEE Conference on Decision and Control. Sydney, Australia:IEEE, 2000. 4765-4770
    [14]
    Swaroop D, Hedrick J K, Yip P P, Gerdes J C. Dynamic surface control for a class of nonlinear systems. IEEE Transactions on Automatic Control, 2000, 45(10):1893-1899
    [15]
    Gao D X, Sun Z Q, Du T R. Dynamic surface control for hypersonic aircraft using fuzzy logic system. In:Proceedings of the 1st IEEE International Conference on Automation and Logistics. Jinan, China:IEEE, 2007. 2314-2319
    [16]
    Utkin V. Variable structure systems with sliding modes. IEEE Transactions on Automatic Control, 1977, 22(2):212-222
    [17]
    Zhou Y X, Wu Y X, Hu Y M. Robust backstepping sliding mode control of a class of uncertain MIMO nonlinear systems. In:Proceedings of the 6th IEEE International Conference on Control and Automation. Guangzhou, China:IEEE, 2007. 1916-1921
    [18]
    Zhu Kai, Qi Nai-Ming, Qin Chang-Mao. Adaptive sliding mode controller design for BTT missile based on backstepping control. Journal of Astronautics, 2011, 31(3):769-773(in Chinese)
    [19]
    Plestan F, Shtessel Y, Bregeault V, Poznyak A. New methodologies for adaptive sliding mode control. International Journal of Control, 2010, 83(9):1907-1919
    [20]
    Park J, Sandberg I W. Universal approximation using radial basis function networks. Neural Computation, 1991, 3(2):246-257
    [21]
    Cybenko G. Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals, and Systems, 1989, 2(4):303-314
    [22]
    Hornik K, Stinchcombe M, White H. Multilayer feedforward networks are universal approximators. Neural Networks, 1989, 2(5):359-366
    [23]
    Hu Y N, Jin Y Q, Cui P Y. RBF NN-based backstepping control for strict feedback block nonlinear system and its application. Advances in Neural Networks ISNN 2004 Lecture Notes in Computer Science, 2004, 3174:129-137
    [24]
    Shaughnessy J D, Pinckney S Z, McMinn J D, Cruz C I, Kelley M L. Hypersonic Vehicle Simulation Model:Winged-cone Configuration, Technical Report TM-102610, NASA, USA, 1990.
    [25]
    Keshmiri S, Mirmirani M D. Six-DOF modeling and simulation of a generic hypersonic vehicle for conceptual design studies. Modeling and Simulation Technologies Conference and Exhibit, 2004, 1-12
    [26]
    Slotine J E, Li W P. Applied Nonlinear Control. Englewood Cliff, NJ:Prentice Hall, 1991. 290-292
    [27]
    Levant A. Higher-order sliding modes, differentiation and outputfeedback control. International Journal of Control, 2003, 76(9):924-941

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (1088) PDF downloads(8) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return