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Adaptive sliding mode consensus control based on neural network for singular fractional order multi-agent systems

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  • Zhang, Xuefeng
  • Chen, Shunan
  • Zhang, Jin-Xi

Abstract

In this paper, a suitable state feedback sliding mode controller is designed for the singular fractional order multi-agent systems (SFOMASs) with uncertainty, in order to realize the consensus problem of multi-agent. First, the sliding mode of the designed SFOMAS is in the form of singular systems. The criterion for the admissible consensus of sliding mode is given by using linear matrix inequality (LMI), and an adaptive law based on radial basis function neural network (RBFNN) is established to ensure the accessibility of SFOMASs. Then, a special method is studied to make the sliding mode of the designed SFOMAS normalization. A sufficient condition for the stability and consensus of sliding mode is given by using LMI, and an adaptive law based on RBFNN is established to ensure the accessibility of SFOMAS. Finally, two numerical examples show the applicability of the proposed method.

Suggested Citation

  • Zhang, Xuefeng & Chen, Shunan & Zhang, Jin-Xi, 2022. "Adaptive sliding mode consensus control based on neural network for singular fractional order multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    • Handle: RePEc:eee:apmaco:v:434:y:2022:i:c:s0096300322005161
    DOI: 10.1016/j.amc.2022.127442
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    References listed on IDEAS

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    1. Jun Hu & Hongxu Zhang & Hongjian Liu & Xiaoyang Yu, 2021. "A survey on sliding mode control for networked control systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(6), pages 1129-1147, April.
    2. Tavazoei, Mohammad Saleh & Haeri, Mohammad, 2009. "A note on the stability of fractional order systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1566-1576.
    3. Jun Shen & James Lam, 2014. "State feedback control of commensurate fractional-order systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(3), pages 363-372.
    4. Guoliang Wei & Linlin Liu & Licheng Wang & Derui Ding, 2020. "Event-triggered control for discrete-time systems with unknown nonlinearities: an interval observer-based approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(6), pages 1019-1031, April.
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    Cited by:

    1. Arockia Samy, Stephen & Anbalagan, Pratap, 2023. "Disturbance observer-based integral sliding-mode control design for leader-following consensus of multi-agent systems and its application to car-following model," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Chen, Jiqing & Zhang, Haiyan & Zhu, Tongtong & Pan, Shangtao, 2024. "Trajectory tracking control of a manipulator based on an immune algorithm-optimized neural network in the presence of unknown backlash-like hysteresis," Applied Mathematics and Computation, Elsevier, vol. 470(C).
    3. Yao Lu, 2023. "The Maximum Correntropy Criterion-Based Identification for Fractional-Order Systems under Stable Distribution Noises," Mathematics, MDPI, vol. 11(20), pages 1-18, October.

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