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Nov.  2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2019  >  6(6): 1417-1427
Huanqing Wang, Wen Bai and Peter Xiaoping Liu, "Finite-time Adaptive Fault-tolerant Control for Nonlinear Systems With Multiple Faults," IEEE/CAA J. Autom. Sinica, vol. 6, no. 6, pp. 1417-1427, Nov. 2019. doi: 10.1109/JAS.2019.1911765
Citation: Huanqing Wang, Wen Bai and Peter Xiaoping Liu, "Finite-time Adaptive Fault-tolerant Control for Nonlinear Systems With Multiple Faults," IEEE/CAA J. Autom. Sinica, vol. 6, no. 6, pp. 1417-1427, Nov. 2019. doi: 10.1109/JAS.2019.1911765
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Finite-time Adaptive Fault-tolerant Control for Nonlinear Systems With Multiple Faults

doi: 10.1109/JAS.2019.1911765
Funds:  This work was supported in part by the National Natural Science Foundation of China (61773072, 61773051, 61761166011, 61773073), in part by the Innovative Talents Project of Liaoning Province of China (LR2016040), and in part by the Natural Science Foundation of Liaoning Province of China (20180550691, 20180550590)
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    Abstract
  • This paper focuses on the problem of adaptive finitetime fault-tolerant control for a class of non-lower-triangular nonlinear systems. The faults encountered in the control system include the actuator faults and the abrupt system fault. By applying backstepping design and neural networks approximation, an adaptive finite-time fault-tolerant control scheme is developed. It is shown that the proposed controller ensures that all signals in the closed-loop system are semi-globally practically finite-time stable and the track-ing error converges to a small neighborhood around the origin within finite time. The simulation is carried out to explain the validity of the developed strategy.

     

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  • [1]
    S. S. Shankara and A. Isidori, " Adaptive control of linearizable systems,” IEEE Trans. Autom. Control, vol. 34, no. 11, pp. 1123–1131, Nov. 1989. doi: 10.1109/9.40741
    [2]
    K. S. Narendra and J. Balakrishnan, " Adaptive control using multiple models,” IEEE Trans. Autom. Control, vol. 42, no. 2, pp. 171–187, Feb. 1997. doi: 10.1109/9.554398
    [3]
    H. F. Chen and L. Guo, Identification and Stochastic Adaptive Control, Springer Science and Business Media, 2012.
    [4]
    P. A. Ioannou and P. V. Kokotovic, Adaptive Systems With Reduced Models, Berlin, Germany: Springer-Verlag, 1983.
    [5]
    J. J. Craig, P. Hsu, and S. S. Sastry, " Adaptive control of mechanical manipulators,” The Int. J. Robotics Research, vol. 6, no. 2, pp. 16–28, Jun. 1987. doi: 10.1177/027836498700600202
    [6]
    M. Krstic, L. Kanellakopoulos, and P. V. Kokotovic, Nonlinear Adaptive Control Design, New York: Wiley, 1995.
    [7]
    K. S. Narendra and A. M. Annaswamy, Stable Adaptive Systems, Courier Corporation, 2012.
    [8]
    A. J. Koshkouei and A. S. I. Zinober, " Adaptive backstepping control of nonlinear systems with unmatched uncertainty,” in Proc. 39th IEEE Conf. Decision and Control, vol. 5, pp. 4765–4770, Dec. 2000.
    [9]
    J. Zhou and C. Wen, " Adaptive backstepping control of uncertain systems,” Electronics Optics and Control, vol. 11, no. 4, pp. 1115–1119, 2010.
    [10]
    W. Sun, H. Gao, and O. Kaynak, " Adaptive backstepping control for active suspension systems with hard constraints,” IEEE/ASME Trans. Mechatronics, vol. 18, no. 3, pp. 1072–1079, Jul. 2013. doi: 10.1109/TMECH.2012.2204765
    [11]
    T. Zhang, S. S. Ge, and C. C. Hang, " Adaptive neural network control for strict-feedback nonlinear systems using backstepping design,” Automatica, vol. 36, no. 12, pp. 1835–1846, Dec. 2000. doi: 10.1016/S0005-1098(00)00116-3
    [12]
    X. Luo, M. Zhou, S. Li, Y. Xia, Z. H. You, Q. Zhu, and H. Leung, " Incorporation of efficient second-order solvers into latent factor models for accurate prediction of missing QoS data,” IEEE Trans. Cybernetics, vol. 48, no. 4, pp. 1216–1228, Apr. 2018. doi: 10.1109/TCYB.2017.2685521
    [13]
    L. Jin, S. Li, H. M. La, and X. Luo, " Manipulability optimization of redundant manipulators using dynamic neural networks,” IEEE Trans. Industrial Electronics, vol. 64, no. 6, pp. 4710–4720, Feb. 2017. doi: 10.1109/TIE.2017.2674624
    [14]
    T. Gao, Y. J. Liu, L. Liu, and D. Li, " Adaptive neural network-based control for a class of nonlinear pure-feedback systems with time-varying full state constraints,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 923–933, Jul. 2018. doi: 10.1109/JAS.2018.7511195
    [15]
    L. Jin, S. Li, X. Luo, and Y. M. Li, " Neural dynamics for cooperative control of redundant robot manipulators,” IEEE Trans. Industrial Informatics, vol. 14, no. 9, pp. 3812–3821, Jan. 2018. doi: 10.1109/TII.2018.2789438
    [16]
    Y. Y. Zhang, S. Li, J. Gui, and X. Luo, " Velocity-level control with compliance to acceleration-level constraints: a novel scheme for manipulator redundancy resolution,” IEEE Trans. Industrial Informatics, vol. 14, no. 3, pp. 921–930, Aug. 2017.
    [17]
    M. Chen, S. S. Ge, and B. V. E. How, " Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities,” IEEE Trans. Neural Networks, vol. 21, no. 5, pp. 796–812, Mar. 2010. doi: 10.1109/TNN.2010.2042611
    [18]
    S. Li, M. C. Zhou, and X. Luo, " Modified primal-dual neural networks for motion control of redundant manipulators with dynamic rejection of harmonic noises,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 10, pp. 4791–4801, Dec. 2018. doi: 10.1109/TNNLS.2017.2770172
    [19]
    X. Luo, J. Sun, Z. Wang, S. Li, and M. Shang, " Symmetric and nonnegative latent factor models for undirected, high-dimensional, and sparse networks in industrial applications,” IEEE Trans. Industrial Informatics, vol. 13, no. 6, pp. 3098–3107, Jul. 2017. doi: 10.1109/TII.2017.2724769
    [20]
    H. Yang and J. Liu, " An adaptive RBF neural network control method for a class of nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 2, pp. 457–462, Feb. 2018. doi: 10.1109/JAS.2017.7510820
    [21]
    X. Luo, M. Zhou, S. Li, and M. Shang, " An inherently nonnegative latent factor model for high-dimensional and sparse matrices from industrial applications,” IEEE Trans. Industrial Informatics, vol. 14, no. 5, pp. 2011–2022, Oct. 2018. doi: 10.1109/TII.2017.2766528
    [22]
    J. R. Noriega and H. Wang, " A direct adaptive neural-network control for unknown nonlinear systems and its application,” IEEE Trans. Neural Networks, vol. 9, no. 1, pp. 27–34, Jan. 1998. doi: 10.1109/72.655026
    [23]
    H. X. Li and S. Tong, " A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems,” IEEE Trans. Fuzzy Systems, vol. 11, no. 1, pp. 24–34, Feb. 2003. doi: 10.1109/TFUZZ.2002.806314
    [24]
    X. Luo, M. Zhou, Y. Xia, Q. Zhu, A. C. Ammari, and A. Alabdulwahab, " Generating highly accurate predictions for missing QoS data via aggregating nonnegative latent factor models,” IEEE Trans. Neural Networks and Learning Systems, vol. 27, no. 3, pp. 524–537, Apr. 2016. doi: 10.1109/TNNLS.2015.2412037
    [25]
    X. Luo, M. Zhou, S. Li, Z. You, Y. Xia, and Q. Zhu, " A nonnegative latent factor model for large-scale sparse matrices in recommender systems via alternating direction method,” IEEE Trans. Neural Networks and Learning Systems, vol. 27, no. 3, pp. 579–592, May 2016. doi: 10.1109/TNNLS.2015.2415257
    [26]
    Y. J. Liu and W. Wang, " Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems,” Information Sciences, vol. 177, no. 18, pp. 3901–3917, Sep. 2007. doi: 10.1016/j.ins.2007.03.005
    [27]
    L. Liu, Y. J. Liu, and S. C. Tong, " Fuzzy based multi-error constraint control for switched nonlinear systems and its applications,” IEEE Trans. Fuzzy Systems, Nov. 2018.
    [28]
    D. P. Li and D. J. Li, " Adaptive neural tracking control for an uncertain state constrained robotic manipulator with unknown time-varying delays,” IEEE Trans. Systems,Man,and Cybernetics:Systems, vol. 99, pp. 1–10, Jun. 2017.
    [29]
    H. Q. Wang, P. X. P. Liu, X. J. Xie, T. Hayat, and F. E. Alsaadi, " Adaptive fuzzy asymptotical tracking control of nonlinear systems with unmodeled dynamics and quantized actuator,” Information Sciences, Apr. 2018.
    [30]
    N. Zerari, M. Chemachema, and N. Essounbouli, " Neural network based adaptive tracking control for a class of pure feedback nonlinear systems with input saturation,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 278–290, Sep. 2019. doi: 10.1109/JAS.2018.7511255
    [31]
    S. Z. He, S. H. Tan, C. C. Hang, and P. Z. Wang, " Design of an online rule-adaptive fuzzy control system,” IEEE Int. Conf. Fuzzy Systems, pp. 83–91, Aug. 1992.
    [32]
    X. D. Tang, G. Tao, and S. M. Joshi, " Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application,” Automatica, vol. 43, no. 11, pp. 1869–1883, Nov. 2007. doi: 10.1016/j.automatica.2007.03.019
    [33]
    M. Chen, X. Liu, and H. Wang, " Adaptive robust fault-tolerant control for nonlinear systems with prescribed performance,” Nonlinear Dynamics, vol. 81, no. 4, pp. 1727–1739, Apr. 2015. doi: 10.1007/s11071-015-2102-5
    [34]
    E. E. Yaz and A. Azemi, " Actuator fault detection and isolation in nonlinear systems using LMIs and LMEs,” in Proc. American Control Conf., vol. 3, pp. 1590–1594, Aug. 1998.
    [35]
    M. R. Napolitano, Y. An, and B. A. Seanor, " A fault tolerant flight control system for sensor and actuator failures using neural networks,” Aircraft Design, vol. 3, no. 2, pp. 103–128, Jun. 2000. doi: 10.1016/S1369-8869(00)00009-4
    [36]
    Q. K. Shen, B. Jiang, P. Shi, and J. Zhao, " Cooperative adaptive fuzzy tracking control for networked unknown nonlinear multiagent systems with timevarying actuator faults,” IEEE Tran. Fuzzy Systems, vol. 22, no. 3, pp. 494–504, Apr. 2014. doi: 10.1109/TFUZZ.2013.2260757
    [37]
    P. Mhaskar, C. McFall, A. Gani, P. D. Christofides, and J. F. Davis, " Isolation and handling of actuator faults in nonlinear systems,” Automatica, vol. 44, no. 1, pp. 53–62, Jan. 2008. doi: 10.1016/j.automatica.2007.05.006
    [38]
    H. Wang, X. Liu, P. X. Liu, and S. Liu, " Backstepping adaptive fuzzy control of uncertain nonlinear systems against actuator faults,” Information Sciences, vol. 7, pp. 60–74, 2009.
    [39]
    H. Noura, D. Theilliol, and D. Sauter, " Actuator fault-tolerant control design: demonstration on a three-tank-system,” Int. J. Systems Science, vol. 31, no. 9, pp. 1143–1155, Nov. 2000. doi: 10.1080/002077200418414
    [40]
    R. H. Chen and J. L. Speyer, " Sensor and actuator fault reconstruction,” J. Guidance Control and Dynamics, vol. 27, no. 2, pp. 186–196, 2004. doi: 10.2514/1.9163
    [41]
    Y. Li and S. Tong, " Adaptive neural networks decentralized FTC design for nonstrict-feedback nonlinear interconnected large-scale systems against actuator faults,” IEEE Trans. Neural Networks and Learning Systems, vol. 28, no. 11, pp. 2541–2554, Aug. 2017. doi: 10.1109/TNNLS.2016.2598580
    [42]
    Y. X. Li and G. H. Yang, " Adaptive fuzzy decentralized control for a class of large-scale nonlinear systems with actuator faults and unknown dead zones,” IEEE Trans. Systems,Man,and Cybernetics:Systems, vol. 47, no. 5, pp. 729–740, Feb. 2017. doi: 10.1109/TSMC.2016.2521824
    [43]
    Y. Han, J. D. Biggs, and N. Cui, " Adaptive fault-tolerant control of spacecraft attitude dynamics with actuator failures,” J. Guidance,Control,and Dynamics, vol. 38, no. 10, pp. 2033–2042, 2015. doi: 10.2514/1.G000921
    [44]
    Y. Hong, " Finite-time stabilization and stabilizability of a class of controllable systems,” Systems and Control Letters, vol. 46, no. 4, pp. 231–236, Jul. 2002. doi: 10.1016/S0167-6911(02)00119-6
    [45]
    Y. Hong and Z. P. Jiang, " Finite-time stabilization of nonlinear systems with parametric and dynamic uncertainties,” IEEE Trans. Autom. Control, vol. 51, no. 12, pp. 1950–1956, Dec. 2006. doi: 10.1109/TAC.2006.886515
    [46]
    X. Huang, W. Lin, and B. Yang, " Global finite-time stabilization of a class of uncertain nonlinear systems,” Automatica, vol. 41, no. 5, pp. 881–888, May 2005. doi: 10.1016/j.automatica.2004.11.036
    [47]
    J. S. Huang, C. Y. Wen, W. Wang, and Y. D. Song, " Adaptive finite-time consensus control of a group of uncertain nonlinear mechanical systems,” Automatica, vol. 51, pp. 292–301, Jan. 2015. doi: 10.1016/j.automatica.2014.10.093
    [48]
    Y. Hong, J. Wang, and D. Cheng, " Adaptive finite-time control of nonlinear systems with parametric uncertainty,” IEEE Trans. Autom. Control, vol. 51, no. 5, pp. 858–862, May 2006. doi: 10.1109/TAC.2006.875006
    [49]
    A. M. Zou, K. D. Kumar, Z. G. Hou, and X. Liu, " Finite-time attitude tracking control for spacecraft using terminal sliding mode and chebyshev neural network,” IEEE Trans. Systems,Man,and Cybernetics,Part B (Cybernetics), vol. 41, no. 4, pp. 950–963, Jan. 2011. doi: 10.1109/TSMCB.2010.2101592
    [50]
    N. Bigdeli and H. A. Ziazi, " Finite-time fractional-order adaptive intelligent backstepping sliding mode control of uncertain fractional-order chaotic systems,” J. Franklin Institute, vol. 354, no. 1, pp. 160–183, Jan. 2017. doi: 10.1016/j.jfranklin.2016.10.004
    [51]
    F. Wang and X. Zhang, " Adaptive finite time control of nonlinear systems under time-varying actuator failures,” IEEE Trans. Systems,Man,and Cybernetics:Systems, Sep. 2018.
    [52]
    F. Wang, B. Chen, Y. M. Sun, and C. Lin, " Finite time control of switched stochastic nonlinear systems,” Fuzzy Sets and Systems, vol. 365, pp. 140–152, Jun. 2019. doi: 10.1016/j.fss.2018.04.016
    [53]
    F. Wang, Z. Liu, Y. Zhang, and C. L. P. Chen, " Adaptive finite-time control of stochastic nonlinear systems with actuator failures,” Fuzzy Sets and Systems, Dec. 2018.
    [54]
    L. Liu, Y. J. Liu, and S. Tong, " Neural networks-based adaptive finite-time fault-tolerant control for a class of strict-feedback switched nonlinear systems,” IEEE Trans. Cybernetics, vol. 99, pp. 1–10, May 2018.
    [55]
    H. Q. Wang, P. X. P. Liu, X. D. Zhao, and X. P. Liu, " Adaptive fuzzy finite-time control of nonlinear systems with actuator faults,” IEEE Trans. Cybernetics, May 2019. doi: 10.1109/TCYB.2019.2902868
    [56]
    S. He and J. Song, " Finite-time sliding mode control design for a class of uncertain conic nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 809–816, Sep. 2017. doi: 10.1109/JAS.2017.7510643
    [57]
    H. H. Wang, B. Chen, C. Lin, and Y. M. Sun, " Adaptive finite-time control for a class of uncertain high-order non-linear systems based on fuzzy approximation,” IET Control Theory and Applications, vol. 11, no. 5, pp. 677–684, Mar. 2017. doi: 10.1049/iet-cta.2016.0947
    [58]
    F. Wang. B. Chen. X. Liu, and C. Lin, " Finite-time adaptive fuzzy tracking control design for nonlinear systems,” IEEE Trans. Fuzzy Systems, vol. 26, no. 3, pp. 1207–1216, Jun. 2018. doi: 10.1109/TFUZZ.2017.2717804
    [59]
    X. J. Li and G. H. Yang, " Robust adaptive fault-tolerant control for uncertain linear systems with actuator failures,” IET Control Theory and Applications, vol. 6, no. 10, pp. 1544–1551, Jul. 2012. doi: 10.1049/iet-cta.2011.0599
    [60]
    S. C. Tong, B. Y. Huo, and Y. M. Li, " Observer-based adaptive decentralized fuzzy fault-tolerant control of nonlinear large-scale systems with actuator failures,” IEEE Trans. Fuzzy Systems, vol. 22, no. 1, pp. 1–15, Jan. 2014. doi: 10.1109/TFUZZ.2013.2241770
    [61]
    B. Y. Huo, S. C. Tong, and Y. M. Li, " Adaptive fuzzy fault-tolerant output feedback control for uncertain nonlinear systems with actuator faults,” Int. J. Control,Automation,and Systems, vol. 44, no. 12, pp. 2365–2376, Jul. 2013.
    [62]
    P. Li and G. Yang, " Backstepping adaptive fuzzy control of uncertain nonlinear systems against actuator faults,” J. Control Theory and Applications, vol. 7, no. 3, pp. 248–256, Aug. 2009. doi: 10.1007/s11768-009-8074-6
    [63]
    B. Chen, X. P. Liu, and S. S. Ge, " Adaptive fuzzy control of a class of nonlinear systems by fuzzy approximation approach,” IEEE Trans. Fuzzy Systems, vol. 20, no. 6, pp. 1012–1021, Mar. 2012. doi: 10.1109/TFUZZ.2012.2190048
    [64]
    Y. M. Su, B. Chen, C. Lin, H. H. Wang, and S. W. Zhou, " Adaptive neural control for a class of stochastic nonlinear systems by backstepping approach,” Information Sciences, vol. 369, pp. 748–764, Nov. 2016. doi: 10.1016/j.ins.2016.06.010
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    Highlights

    • In this paper, an adaptive fault-tolerant finite-time control is considered for a class of non-lower-triangular nonlinear systems by using the approximation and structural properties of radial basis function neural networks (RBFNN).
    • According to the finite-time stability theoretics and the approximation of NNs, a finite-time fault-tolerant tracking control technique is designed with the utilization of backstepping.
    • The proposed fault-tolerant control controller ensures that all signals in the closed-loop system are semi-globally practically finite-time stable and the tracking error converges to a small neighborhood around origin within finite time.
    • The actuator faults and the abrupt system fault are considered in the control system, simultaneously

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