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Volume 8 Issue 6
Jun.  2021

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Q. L. Wang, C. Y. Sun, "Distributed Asymptotic Consensus in Directed Networks of Nonaffine Systems With Nonvanishing Disturbance," IEEE/CAA J. Autom. Sinica, vol. 8, no. 6, pp. 1133-1140, Jun. 2021. doi: 10.1109/JAS.2021.1004021
Citation: Q. L. Wang, C. Y. Sun, "Distributed Asymptotic Consensus in Directed Networks of Nonaffine Systems With Nonvanishing Disturbance," IEEE/CAA J. Autom. Sinica, vol. 8, no. 6, pp. 1133-1140, Jun. 2021. doi: 10.1109/JAS.2021.1004021

Distributed Asymptotic Consensus in Directed Networks of Nonaffine Systems With Nonvanishing Disturbance

doi: 10.1109/JAS.2021.1004021
Funds:  This work was supported in part by the National Natural Science Foundation of China (61973074, 61921004, U1713209)
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  • In this paper the distributed asymptotic consensus problem is addressed for a group of high-order nonaffine agents with uncertain dynamics, nonvanishing disturbances and unknown control directions under directed networks. A class of auxiliary variables are first introduced which forms second-order filters and induces all measurable signals of agents’ states. In view of this property, a distributed robust integral of the sign of the error (DRISE) design combined with the Nussbaum-type function is presented that guarantees not only the desired asymptotic consensus, but also the uniform boundedness of all closed-loop variables. Compared with the traditional sliding mode control (SMC) technique, the main feature of our approach is that the integral operation in the proposed control algorithm is designed to be adopted in a continuous manner and ensures less chattering behavior. Simulation results for a group of Duffing-Holmes chaotic systems are employed to verify our theoretical analysis.

     

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  • [1]
    G. Wen, Z. Duan, G. Chen, and W. Yu, “Consensus tracking of multi-agent systems with Lipschitz-type node dynamics and switching topologies,” IEEE Trans. Circuits and Systems (I), vol. 61, no. 2, pp. 499–511, 2014.
    [2]
    W. Yu, G. Chen, and M. Cao, “Some necessary and sufficient conditions for second-order consensus in multi-agent dynamical systems,” Automatica, vol. 46, no. 6, pp. 1089–1095, 2010. doi: 10.1016/j.automatica.2010.03.006
    [3]
    Z. Li, L. Gao, W. Chen, and Y. Xu, “Distributed adaptive cooperative tracking of uncertain nonlinear fractional-order multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 292–300, 2019.
    [4]
    C. Zhang, L. Chang, and X. Zhang, “Leader-follower consensus of upper-triangular nonlinear multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 2, pp. 210–217, 2014. doi: 10.1109/JAS.2014.7004552
    [5]
    Y. Chen, R. Yu, Y. Zhang, and C. Liu, “Circular formation flight control for unmanned aerial vehicles with directed network and external disturbance,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 505–516, 2019.
    [6]
    C. Wang and H. Ji, “Robust consensus tracking for a class of heterogeneous second-order nonlinear multi-agent systems,” Int. J. Robust and Nonlinear Control, vol. 25, no. 17, pp. 3367–3383, 2015. doi: 10.1002/rnc.3269
    [7]
    L. Chen and Q. Wang, “Adaptive robust control for a class of uncertain mimo non-affine nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 3, no. 1, pp. 105–112, 2016. doi: 10.1109/JAS.2016.7373768
    [8]
    C. Wang, X. Wang, and H. Ji, “A continuous leader-following consensus control strategy for a class of uncertain multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 2, pp. 187–192, 2014. doi: 10.1109/JAS.2014.7004549
    [9]
    Q. Wang, C. Sun, and X. Xin, “Robust consensus tracking of linear multiagent systems with input saturation and input-additive uncertainties,” Int. J. Robust and Nonlinear Control, vol. 27, no. 14, pp. 2393–2409, 2016.
    [10]
    W. Liu and J. Huang, “Adaptive leader-following consensus for a class of higher-order nonlinear multi-agent systems with directed switching networks,” Automatica, vol. 79, pp. 84–92, 2017. doi: 10.1016/j.automatica.2017.02.010
    [11]
    C. Hua, X. You, and X. Guan, “Leader-following consensus for a class of high-order nonlinear multi-agent systems,” Automatica, vol. 73, pp. 138–144, 2016. doi: 10.1016/j.automatica.2016.06.025
    [12]
    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, 2018.
    [13]
    H. Lin, B. Zhao, D. Liu, and C. Alippi, “Data-based fault tolerant control for affine nonlinear systems through particle swarm optimized neural networks,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 954–964, 2020. doi: 10.1109/JAS.2020.1003225
    [14]
    Y. Yang and D. Yue, “Distributed tracking control of a class of multi-agent systems in non-affine pure-feedback form under a directed topology,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 169–180, 2018. doi: 10.1109/JAS.2017.7510382
    [15]
    Y. Wang, Y. Song, and H. David, “Zero-error consensus tracking with preassignable convergence for nonaffine multiagent systems,” IEEE Trans. on Cybernetics, vol. 15, no. 3, pp. 1300–1310, 2021. doi: 10.1109/TCYB.2019.2893461
    [16]
    B. Fan, Q. Yang, S. Jagannathan, and Y. Sun, “Output-constrained control of nonaffine multiagent systems with partially unknown control directions,” IEEE Trans. Autom. Control, vol. 64, no. 9, pp. 3936–3942, 2019. doi: 10.1109/TAC.2019.2892391
    [17]
    S. Reza and W. Wang, “Distributed adaptive FBC of uncertain nonaffine multiagent systems preceded by unknown input nonlinearities with unknown gain sign,” IEEE Trans. Systems,Man and Cybernetics:Systems, vol. 50, no. 8, pp. 3036–3046, 2020.
    [18]
    M. Chen and S. Ge, “Direct adaptive neural control for a class of uncertain nonaffine nonlinear systems based on disturbance observer,” IEEE Trans. Cybernetics, vol. 43, no. 4, pp. 1213–1225, 2013. doi: 10.1109/TSMCB.2012.2226577
    [19]
    B. Ren, Q. Zhong, and J. Chen, “Robust control for a class of nonaffine nonlinear systems based on the uncertainty and disturbance estimator,” IEEE Trans. Industrial Informatics, vol. 62, no. 9, pp. 5881–5888, 2015. doi: 10.1109/TIE.2015.2421884
    [20]
    M. Jang, C. Chen, and Y. Tsao, “Sliding mode control for active magnetic bearing system with flexible rotor,” Journal of the Franklin Institute, vol. 342, no. 4, pp. 401–419, 2005. doi: 10.1016/j.jfranklin.2005.01.006
    [21]
    Q. Shen, P. Shi, and Y. Shi, “Distributed adaptive fuzzy control for nonlinear multiagent systems via sliding mode observers,” IEEE Trans. Cybernetics, vol. 46, no. 12, pp. 3086–3097, 2016. doi: 10.1109/TCYB.2015.2496963
    [22]
    Y. Li, G. Yang, and S. Tong, “Fuzzy adaptive distributed event-triggered consensus control of uncertain nonlinear multiagent systems,” IEEE Trans. Systems,Man and Cybernetics:Systems, vol. 49, no. 9, pp. 1777–1786, 2019. doi: 10.1109/TSMC.2018.2812216
    [23]
    Q. Xu, “Precision motion control of piezoelectric nanopositioning stage with chattering-free adaptive sliding mode control,” IEEE Trans. Autom. Science and Engineering, vol. 14, no. 1, pp. 238–248, 2016.
    [24]
    A. Levant, “Higher-order sliding modes, differentiation and outputfeedback control,” Int. J. Control, vol. 76, no. 9–10, pp. 924–941, 2003. doi: 10.1080/0020717031000099029
    [25]
    P. Tiwari, S. Janardhanan, and M. Un Nabi, “Rigid spacecraft attitude control using adaptive integral second order sliding mode,” Aerospace Science and Technology, vol. 42, pp. 50–57, 2015. doi: 10.1016/j.ast.2014.11.017
    [26]
    S. Ali, R. Samar, M. Shah, A. Bhatti, and K. Munawar, “Higher-order sliding mode based lateral guidance for unmanned aerial vehicles,” Transactions of the Institute of Mesasurement and Control, vol. 39, no. 5, pp. 715–727, 2017. doi: 10.1177/0142331215619972
    [27]
    B. Xian and Y. Zhang, “Continuous asymptotically tracking control for a class of nonaffine-in-input system with non-vanishing disturbance,” IEEE Trans. Autom. Control, vol. 62, no. 11, pp. 6019–6025, 2017. doi: 10.1109/TAC.2017.2704025
    [28]
    Q. Wang, H. Psillakis, and C. Sun, “Adaptive cooperative control with guaranteed convergence in time-varying networks of nonlinear dynamical systems,” IEEE Trans. Cybernetics, vol. 50, no. 12, pp. 5035–5046, 2020. doi: 10.1109/TCYB.2019.2916563
    [29]
    R. Nussbaum, “Some remarks on a conjecture in parameter adaptive control,” Systems &Control Letters, vol. 3, no. 5, pp. 243–246, 1983.
    [30]
    G. Shi and K. Johansson, “Robust consensus for continuous-time multiagent dynamics,” SIAM J. Control Optim., vol. 51, no. 5, pp. 3673–3691, 2013. doi: 10.1137/110841308
    [31]
    A. Filippov, Differential Equations With Discontinuous Righthand Sides: Control Systems, Netherlands: Springer Science & Business Media, 2013.
    [32]
    N. Fischer, R. Kamalapurkar, and W. Dixon, “Lasalle-Yoshizawa corollaries for nonsmooth systems,” IEEE Trans. Autom. Control, vol. 58, no. 9, pp. 2333–2338, 2013. doi: 10.1109/TAC.2013.2246900
    [33]
    Q. Wang, H. Psillakis, C. Sun, and F. Lewis, “Adaptive NN distributed control for time-varying networks of nonlinear agents with antagonistic interactions,” IEEE Trans. Neural Networks and Learning Systems, to be pulished, 2020.

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    Highlights

    • This is the first work to consider the leaderless consensus problem of high-order nonaffine agents with uncertain dynamics, nonvanishing disturbance, and unknown control directions, in contrast to existing results for consensus of nonaffine agents.
    • A new DRISE design combined with the Nussbaum-type function is first proposed to guarantee not only the desired asymptotic consensus, but also the uniform boundedness of all closed-loop variables.
    • Different from existing results on consensus of agents with nonvanishing disturbance, in this work the integral operation in the proposed control algorithm is adopted to incorporate in a continuous manner and ensure less chattering behavior.

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