2606004145
  • Open Access
  • Article

Observer-Based Leader-Follower Coordination in Fractional-Order Multi-Manipulator Systems

  • Wen Wang 1,   
  • Shang Hua 2,   
  • Huanyu Zhao 2,*

Received: 10 Mar 2026 | Revised: 09 May 2026 | Accepted: 04 Jun 2026 | Published: 19 Aug 2026

Abstract

This study focuses on the leader-follower control problem of fractional-order multi-manipulator systems in which certain state components of the follower manipulators are unmeasurable. To address this issue, a nonlinear state observer is developed to estimate the unknown states from system outputs. The design parameters of both the observer and the leader-follower control law are then determined using the linear matrix inequality (LMI) framework. Furthermore, by applying Lyapunov stability theory, sufficient conditions ensuring leader-follower consensus are established. The effectiveness and practicality of the proposed approach are subsequently demonstrated through numerical simulations.

References 

  • 1.

    Min, R.; Zhang, S. Dynamics modelling and stability analysis of a multi-mobile robotic manipulator system. J. Dyn. Control 2023, 21, 107–113.

  • 2.

    Chang, T.; Zhao, L. Asymptotic tracking control for robot manipulators systems with time-varying output constraints. Modul. Mach. Tool Autom. Manuf. Tech. 2024, 1, 72–76. (In Chinese)

  • 3.

    Wu, M.; Yang, J.; Yu, J. Region constrained consensus control of flexible-joint robot manipulators. Syst. Sci. Math. 2024, 44, 60–70.

  • 4.

    Wang, X.; Wang, X.; Wu, Q. Review of motion planning methods for mobile manipulators. Comput. Meas. Control 2024, 32, 1–8. (In Chinese)

  • 5.

    Zhang, Y.; Jiang, Y.; Zhang, W.; et al. Distributed coordinated tracking control for multi-manipulator systems under intermittent communications. Nonlinear Dyn. 2022, 107, 3573–3591.

  • 6.

    Wang, H.; Gao, F.; Li, M.; et al. ESO-based robust model predictive control for undersea vehicle manipulator system. J. Underw. Unmanned Syst. 2023, 31, 827–838.

  • 7.

    Fu, H.; He, H.; Chen, Y. Event-triggered cooperative tracking control of multi-agent systems with a dynamic leader via approximate dynamic programming. IEEE Trans. Artif. Intell. 2024, 5, 2752–2765.

  • 8.

    Sun, H.; Xia, R.; Yu, A. Fully distributed event-triggered consensus for a class of second-order nonlinear multi-agent systems. Circuits Syst. Signal Process. 2022, 41, 725–742.

  • 9.

    Qiang, J.; Li, L.; Xia, Y. Distributed prescribed-time leader-follower tracking consensus control for high-order nonlinear MASs. Nonlinear Dyn. 2023, 112, 491–505.

  • 10.

    Huang, P.; Di, F.; Xu, J.; et al. Distributed finite-time dynamic event-triggered consensus control for nonlinear multi-agent systems. Int. J. Control Autom. Syst. 2023, 21, 3684–3695.

  • 11.

    Cui, Q.; Liu, K.; Ji, Z.; et al. Finite-time and fixed-time adaptive consensus of multi-agent systems with general linear dynamics. Math. Methods Appl. Sci. 2023, 46, 18560–18578.

  • 12.

    Cai, X.; Zhu, H.; Zhu, X.; et al. Time-varying group formation tracking for nonlinear multi-agent systems under switching topologies. Appl. Intell. 2024, 54, 1909–1921.

  • 13.

    Han, J.; Yu, J.; Yang, W. Regional optimal coverage control of multi-manipulator systems. Microelectron. Comput. 2023, 40, 62–69. (In Chinese)

  • 14.

    Xia, H.; Cui, Q.; Teng, Y.; et al. Multi-manipulator cooperative control based on DMPC. High-Tech Commun. 2023, 33, 428–435. (In Chinese)

  • 15.

    Meng, X.; Wu, A.; Mei, J.; et al. Consensus of multiple manipulators with elastic joints under a directed graph. Sci. China Inf. Sci. 2023, 53, 81–96.

  • 16.

    Zheng, W.; Fu, L.; Wang, H. High-order multi-agent event-driven control in adversarial network environment. Control Theory Appl. 2025, 42, 1875–1883. (In Chinese)

  • 17.

    Mei, J. Distributed consensus for multiple Lagrangian systems with parametric uncertainties and external disturbances under directed graphs. IEEE Trans. Control Netw. Syst. 2020, 7, 648–659.

  • 18.

    Li, F.; Wang, G.; Hou, Y.; et al. Output feedback consensus of nonlinear multi-agent systems under directed topologies. Circuits Syst. Signal Process. 2023, 42, 216–233.

  • 19.

    Rao, S.; Rao, S. Finite-time consensus for leader-follower and leaderless swarms in the presence of malicious agents. Int. J. Control 2022, 96, 2623–2635.

  • 20.

    Lu, L.; Han, T.; Xiao, B.; et al. Distributed observer-based predefined-time consensus control for second-order multi-agent systems. Circuits Syst. Signal Process. 2023, 42, 7099–7116.

  • 21.

    Aldana, C.; Tabarez, L.; Nuño, L.; et al. Leader-follower and leaderless pose consensus of robot networks with variable time-delays and without velocity measurements. Int. J. Control 2022, 96, 2885–2897.

  • 22.

    Liu, Y.; Zhang, H.; Wang, Y.; et al. Adaptive containment control for fractional-order nonlinear multi-agent systems with time-varying parameters. IEEE/CAA J. Autom. Sin. 2022, 9, 1627–1638.

  • 23.

    Yan, X.; Li, K.; Yang, C.; et al. Consensus of fractional-order multi-agent systems via observer-based boundary control. IEEE Trans. Netw. Sci. Eng. 2024, 11, 3370–3382.

  • 24.

    Yavuz, M.; Ozturk, M.; Yaskiran, B. Comparison of fractional order sliding mode controllers on robot manipulator. Int. J. Optim. Control Theor. Appl. 2025, 15, 281–293.

  • 25.

    Qi, Q.; Chen, X.; Wang, D.; et al. Boundary control for consensus in fractional-order multi-agent systems under DoS attacks and actuator failures. Fractal Fract. 2025, 9, 9110745.

  • 26.

    Alsinai, A.; Niazi, A.; Iqbal, M.; et al. Consensus control of fractional-order singular MAS via adaptive pinning under switching topologies. Int. J. Optim. Control Theor. Appl. 2026, 16, 349–369.

  • 27.

    Fiuzy, M.; Rass, S. Consensus control in time varying nonlinear fractional-order multi- agent systems: LMI-driven stability analysis and DoS attack detection. IFAC Pap. Online 2025, 59, 85–90.

  • 28.

    Cao, R.; Mei, J. Group consensus for networked Euler-Lagrangian systems under a directed graph without relative velocity information. Acta Autom. Sin. 2018, 44, 44–51.

  • 29.

    Podlubny, I. Fractional Differential Equations; Academic Press: San Diego, CA, USA, 1999.

  • 30.

    Li, J. Global Mittag-Leffler synchronization of Caputo fractional inertial memristive neural networks. Electron. Technol. Softw. Eng. 2020, 22, 63–65. (In Chinese)

  • 31.

    Ding, M.; Xu, F.; Chen, X. Recursive formulas for the Kronecker quantum cluster algebra with principal coefficients. Sci. China Math. 2023, 66, 1933–1948.

  • 32.

    Duarte-Mermoud, M.A.; Aguila-Camacho, N.; Galleg-Os, J.A.; et al. Using general quadratic Lyapunov functions to prove Lyapunov uniform stability for fractional order systems. Commun. Nonlinear Sci. Numer. Simul. 2015, 20, 650–659.

  • 33.

    Boyd, S.; EI Ghaoui, L.; Feron, E.; et al. Linear Matrix Inequalities in Systems and Control Theory; SIAM: Philadelphia, PA, USA, 1994.

  • 34.

    Wen, G.; Duan, Z.; Chen, G.; et al. Consensus tracking of multi-agent systems with Lipschitz-type node dynamics and switching topologies. IEEE Trans. Circuits Syst. I Regul. Pap. 2014, 61, 499–511.

  • 35.

    Zhang, Y. Research on Distributed Coordinated Tracking Control for Multi-Manipulator Systems under Intermittent Communication. Ph.D. Thesis, Changchun University of Technology, Changchun, China, 2022.

  • 36.

    Li, Y.; Chen, Y.; Podlubny, I. Stability of fractional-order nonlinear dynamic systems: Lyapunov direct method and generalized Mittag-Leffler stability. Comput. Math. Appl. 2010, 59, 1810–1821.

  • 37.

    Shamrooz, S.; Aslam, M.; Liu, H.; et al. Modeling of asynchronous mode-dependent delays in stochastic Markovian jumping modes based on static neural networks for robotic manipulators. IEEE Trans. Autom. Sci. Eng. 2025, 22, 13398–13410.

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How to Cite
Wang, W.; Hua, S.; Zhao, H. Observer-Based Leader-Follower Coordination in Fractional-Order Multi-Manipulator Systems. Complex Systems Stability & Control 2026, 2 (3), 12. https://doi.org/10.53941/cssc.2026.100023.
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