A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Advanced Search
Volume 10 Issue 4
Apr.  2023

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77， TOP 5
Turn off MathJax
Article Contents
Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2023  >  10(4): 1020-1031
Y. Liu and L. Li, “Adaptive leader-follower consensus control of multiple flexible manipulators with actuator failures and parameter uncertainties,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 1020–1031, Apr. 2023. doi: 10.1109/JAS.2023.123093
Citation: Y. Liu and L. Li, “Adaptive leader-follower consensus control of multiple flexible manipulators with actuator failures and parameter uncertainties,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 1020–1031, Apr. 2023. doi: 10.1109/JAS.2023.123093
shu

Adaptive Leader-Follower Consensus Control of Multiple Flexible Manipulators With Actuator Failures and Parameter Uncertainties

doi: 10.1109/JAS.2023.123093
  • 1.

    School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, and also with the Research and Development Center of Precision Electronic Manufacturing Technology, Guangzhou Institute of Modern Industrial Technology, Guangzhou 511458, China

  • 2.

    School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China

Funds:  This work was supported in part by the National Key Research and Development Program of China (2021YFB3202200) and Guangdong Basic and Applied Basic Research Foundation (2020B1515120071, 2021B1515120017)
More Information
    Abstract
  • In this paper, the leader-follower consensus problem for a multiple flexible manipulator network with actuator failures, parameter uncertainties, and unknown time-varying boundary disturbances is addressed. The purpose of this study is to develop distributed controllers utilizing local interactive protocols that not only suppress the vibration of each flexible manipulator but also achieve consensus on joint angle position between actual followers and the virtual leader. Following the accomplishment of the reconstruction of the fault terms and parameter uncertainties, the adaptive neural network method and parameter estimation technique are employed to compensate for unknown items and bounded disturbances. Furthermore, the Lyapunov stability theory is used to demonstrate that followers’ angle consensus errors and vibration deflections in closed-loop systems are uniformly ultimately bounded. Finally, the numerical simulation results confirm the efficacy of the proposed controllers.

     

    • FullText(HTML)
  • loading
    • References(41)
  • [1]
    Z. J. Zhao and Z. J. Liu, “Finite-time convergence disturbance rejection control for a flexible timoshenko manipulator,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 157–168, Jan. 2021. doi: 10.1109/JAS.2020.1003378
    [2]
    Y. Liu, Y. F. Mei, H. Cai, C. R. He, T. Liu, and G. Q. Hu, “Asymmetric input-output constraint control of a flexible variable-length rotary crane arm,” IEEE Trans. Cybern., vol. 52, no. 10, pp. 10582–10591, Oct. 2022. doi: 10.1109/TCYB.2021.3055151
    [3]
    W. He, X. Y. He, M. Zou, and H. Y. Li, “PDE model-based boundary control design for a flexible robotic manipulator with input backlash,” IEEE Trans. Control Syst. Technol., vol. 27, no. 2, pp. 790–797, Mar. 2019. doi: 10.1109/TCST.2017.2780055
    [4]
    Y. Liu, W. K. Zhan, M. L. Xing, Y. L. Wu, R. F. Xu, and X. S. Wu, “Boundary control of a rotating and length-varying flexible robotic manipulator system,” IEEE Trans. Syst. Man Cybern. Syst., vol. 52, no. 1, pp. 377–386, Jan. 2022. doi: 10.1109/TSMC.2020.2999485
    [5]
    Y. H. Ma, X. Y. He, S. Zhang, Y. B. Sun, and Q. Fu, “Adaptive compensation for infinite number of actuator faults and time-varying delay of a flexible manipulator system,” IEEE Trans. Ind. Electron., vol. 69, no. 12, pp. 13141–13150, Dec. 2022. doi: 10.1109/TIE.2021.3139193
    [6]
    T. Chen and J. J. Shan, “Distributed tracking of a class of underactuated lagrangian systems with uncertain parameters and actuator faults,” IEEE Trans. Ind. Electron., vol. 67, no. 5, pp. 4244–4253, May 2020. doi: 10.1109/TIE.2019.2922943
    [7]
    Z. Y. Zuo, Q. L. Han, B. D. Ning, X. H. Ge, and X. M. Zhang, “An overview of recent advances in fixed-time cooperative control of multiagent systems,” IEEE Trans. Ind. Inf., vol. 14, no. 6, pp. 2322–2334, Jun. 2018. doi: 10.1109/TII.2018.2817248
    [8]
    W. Zhao, Y. Liu, and X. Q. Yao, “Adaptive fuzzy containment and vibration control for multiple flexible manipulators with model uncertainties,” IEEE Trans. Fuzzy Syst., 2022, DOI: 10.1109/TFUZZ.2022.3199573
    [9]
    Q. L. Wei, X. Wang, X. N. Zhong, and N. Q. Wu, “Consensus control of leader-following multi-agent systems in directed topology with heterogeneous disturbances,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 2, pp. 423–431, Feb. 2021. doi: 10.1109/JAS.2021.1003838
    [10]
    X. Q. Yao, Y. Liu, and W. Zhao, “Adaptive boundary vibration control and angle tracking consensus of networked flexible Timoshenko manipulator systems,” IEEE Trans. Syst. Man Cybern. Syst., 2022, DOI: 10.1109/TSMC.2022.3221734
    [11]
    S. M. Wang, H. W. Zhang, S. Baldi, and R. X. Zhong, “Leaderless consensus of heterogeneous multiple Euler-Lagrange systems with unknown disturbance,” IEEE Trans. Autom. Control, 2022, DOI: 10.1109/TAC.2022.3172594
    [12]
    T. Chen and J. J. Shan, “Distributed control of multiple flexible manipulators with unknown disturbances and dead-zone input,” IEEE Trans. Ind. Electron., vol. 67, no. 11, pp. 9937–9947, Nov. 2020. doi: 10.1109/TIE.2019.2955417
    [13]
    S. S. Ge, T. H. Lee, and G. Zhu, “Improving regulation of a single-link flexible manipulator with strain feedback,” IEEE Trans. Robot. Autom., vol. 14, no. 1, pp. 179–185, Feb. 1998. doi: 10.1109/70.660869
    [14]
    Y. Liu, F. Guo, X. Y. He, and Q. Hui, “Boundary control for an axially moving system with input restriction based on disturbance observers,” IEEE Trans. Syst. Man Cybern. Syst., vol. 49, no. 11, pp. 2242–2253, Nov. 2019. doi: 10.1109/TSMC.2018.2843523
    [15]
    J. K. Liu and W. He, Distributed Parameter Modeling and Boundary Control of Flexible Manipulators. Singapore, Singapore: Springer, 2018.
    [16]
    Y. Liu, X. B. Chen, Y. F. Mei, and Y. L. Wu, “Observer-based boundary control for an asymmetric output-constrained flexible robotic manipulator,” Sci. China Inf. Sci., vol. 65, no. 3, p. 139203, Mar. 2022. doi: 10.1007/s11432-019-2893-y
    [17]
    A. Pilloni, A. Pisano, Y. Orlov, and E. Usai, “Consensus-based control for a network of diffusion PDEs with boundary local interaction,” IEEE Trans. Autom. Control, vol. 61, no. 9, pp. 2708–2713, Sept. 2016. doi: 10.1109/TAC.2015.2506990
    [18]
    Q. Fu, L. L. Du, G. Z. Xu, and J. R. Wu, “Consensus control for multi-agent systems with distributed parameter models via iterative learning algorithm,” J. Frankl. Inst., vol. 355, no. 10, pp. 4453–4472, Jul. 2018. doi: 10.1016/j.jfranklin.2018.04.033
    [19]
    L. Aguilar, Y. Orlov, and A. Pisano, “Leader-follower synchronization and ISS analysis for a network of boundary-controlled wave PDEs,” IEEE Control Syst. Lett., vol. 5, no. 2, pp. 683–688, Apr. 2021. doi: 10.1109/LCSYS.2020.3004505
    [20]
    T. Chen, H. Wen, and Z. T. Wei, “Distributed attitude tracking for multiple flexible spacecraft described by partial differential equations,” Acta Astronaut., vol. 159, pp. 637–645, Jun. 2019. doi: 10.1016/j.actaastro.2019.02.010
    [21]
    F. M. Han and Y. M. Jia, “Bipartite consensus and distributed boundary control for multiple flexible manipulators associated with signed digraph,” IEEE Trans. Syst. Man Cybern. Syst., vol. 52, no. 5, pp. 3005–3014, May 2022. doi: 10.1109/TSMC.2021.3062165
    [22]
    X. Y. He, W. He, Y. R. Liu, Y. H. Wang, G. Li, and Y. Wang, “Robust adaptive control of an offshore ocean thermal energy conversion system,” IEEE Trans. Syst. Man Cybern. Syst., vol. 50, no. 12, pp. 5285–5295, Dec. 2020. doi: 10.1109/TSMC.2018.2870999
    [23]
    Y. Zou, K. W. Xia, and W. He, “Adaptive fault-tolerant distributed formation control of clustered vertical takeoff and landing UAVs,” IEEE Trans. Aerosp. Electron. Syst., vol. 58, no. 2, pp. 1069–1082, Apr. 2022. doi: 10.1109/TAES.2021.3117368
    [24]
    Y. Zou, H. J. Zhang, and W. He, “Adaptive coordinated formation control of heterogeneous vertical takeoff and landing UAVs subject to parametric uncertainties,” IEEE Trans. Cybern., vol. 52, no. 5, pp. 3184–3195, May 2022. doi: 10.1109/TCYB.2020.3009404
    [25]
    R. H. Yang, L. Liu, and G. Feng, “Leader-following output consensus of heterogeneous uncertain linear multiagent systems with dynamic event-triggered strategy,” IEEE Trans. Syst. Man Cybern. Syst., vol. 52, no. 3, pp. 1626–1637, Mar. 2022. doi: 10.1109/TSMC.2020.3034352
    [26]
    Z. J. Liu, J. K. Liu, and W. He, “Robust adaptive fault tolerant control for a linear cascaded ode-beam system,” Automatica, vol. 98, pp. 42–50, Dec. 2018. doi: 10.1016/j.automatica.2018.09.021
    [27]
    X. L. Yue, X. Y. He, J. K. Liu, and W. He, “Fault-tolerant control for a vibrating nanobeam system,” in Proc. IEEE 58th Conf. Decision and Control, Nice, France, 2019, pp. 3860–3864.
    [28]
    F. F. Cao and J. K. Liu, “Boundary control for PDE flexible manipulators: Accommodation to both actuator faults and sensor faults,” Asian J. Control, vol. 24, no. 4, pp. 1700–1712, Jul. 2022. doi: 10.1002/asjc.2560
    [29]
    Y. Liu, X. B. Chen, Y. L. Wu, H. Cai, and H. Yokoi, “Adaptive neural network control of a flexible spacecraft subject to input nonlinearity and asymmetric output constraint,” IEEE Trans. Neural Netw. Learn. Syst., vol. 33, no. 11, pp. 6226–6234, Nov. 2022. doi: 10.1109/TNNLS.2021.3072907
    [30]
    W. He, X. X. Mu, L. Zhang, and Y. Zou, “Modeling and trajectory tracking control for flapping-wing micro aerial vehicles,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 148–156, Jan. 2021. doi: 10.1109/JAS.2020.1003417
    [31]
    M. Chen, S. Y. Shao, and B. Jiang, “Adaptive neural control of uncertain nonlinear systems using disturbance observer,” IEEE Trans. Cybern., vol. 47, no. 10, pp. 3110–3123, Oct. 2017. doi: 10.1109/TCYB.2017.2667680
    [32]
    Y. Liu, F. J. Liu, Y. F. Mei, and W. W. Wan, “Adaptive neural network vibration control for an output-tension-constrained axially moving belt system with input nonlinearity,” IEEE/ASME Trans. Mechatron., vol. 27, no. 2, pp. 656–665, Apr. 2022. doi: 10.1109/TMECH.2021.3126686
    [33]
    Z. Q. Zuo, J. Zhang, and Y. J. Wang, “Adaptive fault-tolerant tracking control for linear and lipschitz nonlinear multi-agent systems,” IEEE Trans. Ind. Electron., vol. 62, no. 6, pp. 3923–3931, Jun. 2015.
    [34]
    D. Y. Yao, H. Y. Li, and Y. Shi, “Adaptive event-triggered sliding-mode control for consensus tracking of nonlinear multiagent systems with unknown perturbations,” IEEE Trans. Cybern., 2022, DOI: 10.1109/TCYB.2022.3172127
    [35]
    Z. J. Liu, J. K. Liu, and W. He, “Modeling and vibration control of a flexible aerial refueling hose with variable lengths and input constraint,” Automatica, vol. 77, pp. 302–310, Mar. 2017. doi: 10.1016/j.automatica.2016.11.002
    [36]
    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 Netw., vol. 21, no. 5, pp. 796–812, May 2010. doi: 10.1109/TNN.2010.2042611
    [37]
    Y. C. Cao and W. Ren, “Distributed coordinated tracking with reduced interaction via a variable structure approach,” IEEE Trans. Autom. Control, vol. 57, no. 1, pp. 33–48, Jan. 2012. doi: 10.1109/TAC.2011.2146830
    [38]
    Y. J. Wang, Y. D. Song, and F. L. Lewis, “Robust adaptive fault-tolerant control of multiagent systems with uncertain nonidentical dynamics and undetectable actuation failures,” IEEE Trans. Ind. Electron., vol. 62, no. 6, pp. 3978–3988, Jun. 2015.
    [39]
    Z. J. Zhao, Y. Ren, C. X. Mu, T. Zou, and K. S. Hong, “Adaptive neural-network-based fault-tolerant control for a flexible string with composite disturbance observer and input constraints,” IEEE Trans. Cybern., vol. 52, no. 12, pp. 12843–12853, Dec. 2022. doi: 10.1109/TCYB.2021.3090417
    [40]
    Y. Liu, Y. Fu, W. He, and Q. Hui, “Modeling and observer-based vibration control of a flexible spacecraft with external disturbances,” IEEE Trans. Ind. Electron., vol. 66, no. 11, pp. 8648–8658, Nov. 2019. doi: 10.1109/TIE.2018.2884172
    [41]
    G. D. Smith, Numerical Solution of Partial Differential Equations: Finite Difference Methods. Oxford, UK: Oxford University Press, 1985.
    • Related Articles
    • Supplements(0)

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

    Figures(12)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (508) PDF downloads(130) Cited by()

    Highlights

    • Suppress the vibrations of multiple flexible manipulators
    • Realize leader-follower angle consensus for multiple flexible manipulators
    • Handle parameter uncertainties and actuator failures with neural networks
    • Estimate the upper bounds of boundary disturbances and approximation errors

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return