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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2026  > In Press, Accepted Manuscript
X. Zhao and Y. Song, “Distributed cooperative control for common object manipulation with high precision and fast convergence,” IEEE/CAA J. Autom. Sinica, early access, 2026. doi: 10.1109/JAS.2026.126362
Citation: X. Zhao and Y. Song, “Distributed cooperative control for common object manipulation with high precision and fast convergence,” IEEE/CAA J. Autom. Sinica, early access, 2026. doi: 10.1109/JAS.2026.126362
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Distributed Cooperative Control for Common Object Manipulation With High Precision and Fast Convergence

doi: 10.1109/JAS.2026.126362
Funds:  This work was supported in part by the Fundamental Research Funds for the Central Universities (2025CDJZKKYJH17), the National Natural Science Foundation of China (624B2029), the Graduate Research and Innovation Foundation of Chongqing, China (CYB25035), and the China Scholarship Council (202406050215)
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    Abstract
  • Coordinated object manipulation with strict demands on convergence precision and speed remains a major challenge in networked robotic systems. This paper develops a distributed control framework for networked robotic arms to cooperatively manipulate a common object. To achieve the cooperative task distribution in a distributed manner, a prescribed-time estimator (PTE) is developed for each arm to estimate the desired trajectory of the object. A significant merit of the proposed estimator is that zero-error estimation is achieved within the prescribed finite time, with the numerical singularity issue caused by infinite time-varying gains avoided. Together with the estimated task, a novel control policy is synthesized, where the pre-specified convergence precision is ensured within a prescribed time, including the following critical attributes: 1) the settling time and convergence precision are not influenced by the system’s initial conditions, order, or control parameters; and 2) the method is valid for an infinite time interval and allows the system’s initial states to be unknown or random. The effectiveness of the proposed strategy is validated through simulations.

     

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  • [1]
    C. Smith, Y. Karayiannidis, L. Nalpantidis, X. Gratal, P. Qi, D. V. Dimarogonas, and D. Kragic, “Dual arm manipulation-A survey,” Robot. Auton. Syst., vol. 60, no. 10, pp. 1340–1353, Oct. 2012. doi: 10.1016/j.robot.2012.07.005
    [2]
    Y. Lian, X. Xiao, J. Zhang, L. Jin, J. Yu, and Z. Sun, “Neural dynamics for cooperative motion control of omnidirectional mobile manipulators in the presence of noises: A distributed approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 7, pp. 1605–1620, Jul. 2024. doi: 10.1109/JAS.2024.124425
    [3]
    Z. Zhang, J. Mao, H. Tan, Y. Jiang, Y. Feng, Y. Wu, and Y. Wang, “Hybrid force/position control of multi-mobile manipulators for cooperative operation without force measurements,” IEEE Trans. Circuits Syst. I: Reg. Papers, vol. 71, no. 1, pp. 397–410, Jan. 2024. doi: 10.1109/TCSI.2023.3325218
    [4]
    J. Cheng and L. Chen, “The fuzzy neural network control scheme with H∞ tracking characteristic of space robot system with dual-arm after capturing a spin spacecraft,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1417–1424, Sep. 2020. doi: 10.1109/jas.2018.7511180
    [5]
    A. Purushottam, C. Xu, Y. Jung, and J. Ramos, “Dynamic mobile manipulation via whole-body bilateral teleoperation of a wheeled humanoid,” IEEE Robot. Autom. Lett., vol. 9, no. 2, pp. 1214–1221, Feb. 2024. doi: 10.1109/LRA.2023.3334677
    [6]
    H. Zhang, L. Pang, M. Bai, J. Yang, and J. Zhao, “Retinal surgical field realignment based on master-slave dual-arm surgical robot,” IEEE Trans. Autom. Sci. Eng., vol. 21, no. 3, pp. 4743–4752, Jul. 2024. doi: 10.1109/TASE.2023.3301277
    [7]
    W. Gueaieb, S. Al-Sharhan, and M. Bolic, “Robust computationally efficient control of cooperative closed-chain manipulators with uncertain dynamics,” Automatica, vol. 43, no. 5, pp. 842–851, May 2007. doi: 10.1016/j.automatica.2006.10.025
    [8]
    M. Sewlia, C. K. Verginis, and D. V. Dimarogonas, “Cooperative object manipulation under signal temporal logic tasks and uncertain dynamics,” IEEE Robot. Autom. Lett., vol. 7, no. 4, pp. 11561–11568, Oct. 2022. doi: 10.1109/LRA.2022.3200760
    [9]
    S. Erhart and S. Hirche, “Model and analysis of the interaction dynamics in cooperative manipulation tasks,” IEEE Trans. Robot., vol. 32, no. 3, pp. 672–683, Jun. 2016. doi: 10.1109/TRO.2016.2559500
    [10]
    C. Jiao, L. Yu, X. Su, Y. Wen, and X. Dai, “Adaptive hybrid impedance control for dual-arm cooperative manipulation with object uncertainties,” Automatica, vol. 140, Art. no. 110232, Jun. 2022.
    [11]
    C. K. Verginis, M. Mastellaro, and D. V. Dimarogonas, “Robust cooperative manipulation without force/torque measurements: Control design and experiments,” IEEE Trans. Control Syst. Technol., vol. 28, no. 3, pp. 713–729, May 2020. doi: 10.1109/TCST.2018.2885682
    [12]
    P. Culbertson, J.-J. Slotine, and M. Schwager, “Decentralized adaptive control for collaborative manipulation of rigid bodies,” IEEE Trans. Robot., vol. 37, no. 6, pp. 1906–1920, Dec. 2021. doi: 10.1109/TRO.2021.3072021
    [13]
    X. Ren, J. Guo, S. Chen, X. Deng, and Z. Zhang, “Hybrid orientation and position collaborative motion generation scheme for a multiple mobile redundant manipulator system synthesized by a recurrent neural network,” IEEE Trans. Cybern., vol. 54, no. 10, pp. 6035–6047, Oct. 2024. doi: 10.1109/TCYB.2024.3422996
    [14]
    X. Li, J. Luo, S. Li, and F. Wang, “Adaptive fuzzy position and force control for cooperative multimanipulators with system uncertainties and input dead-zone nonlinearities,” IEEE Trans. Fuzzy Syst., vol. 32, no. 12, pp. 6622–6632, Dec. 2024. doi: 10.1109/TFUZZ.2024.3455939
    [15]
    Y. Ren, S. Sosnowski, and S. Hirche, “Fully distributed cooperation for networked uncertain mobile manipulators,” IEEE Trans. Robot., vol. 36, no. 4, pp. 984–1003, Aug. 2020. doi: 10.1109/TRO.2020.2971416
    [16]
    W. S. Cortez, C. K. Verginis, and D. V. Dimarogonas, “A distributed, event-triggered, adaptive controller for cooperative manipulation with rolling contacts,” IEEE Trans. Robot., vol. 39, no. 4, pp. 3120–3133, Aug. 2023. doi: 10.1109/TRO.2023.3268595
    [17]
    E. Tuci, M. H. M. Alkilabi, and O. Akanyeti, “Cooperative object transport in multi-robot systems: A review of the state-of-the-art,” Front. Robot. AI, vol. 5, Art. no. 59, May 2018.
    [18]
    S. Garcia, C. Menghi, P. Pelliccione, T. Berger, and R. Wohlrab, “An architecture for decentralized, collaborative, and autonomous robots,” in Proc. IEEE Int. Conf. Software Architecture, Seattle, USA, 2018, pp. 75-7509.
    [19]
    V.-T. Ngo and Y.-C. Liu, “Object transportation with force-sensorless control and event-triggered synchronization for networked uncertain manipulators,” IEEE Trans. Ind. Electron., vol. 68, no. 1, pp. 902–912, Jan. 2021. doi: 10.1109/TIE.2020.3000123
    [20]
    G.-B. Dai and Y.-C. Liu, “Distributed coordination and cooperation control for networked mobile manipulators,” IEEE Trans. Ind. Electron., vol. 64, no. 6, pp. 5065–5074, Jun. 2017. doi: 10.1109/TIE.2016.2642880
    [21]
    P. B. G. Dohmann and S. Hirche, “Distributed control for cooperative manipulation with event-triggered communication,” IEEE Trans. Robot., vol. 36, no. 4, pp. 1038–1052, Aug. 2020. doi: 10.1109/TRO.2020.2973096
    [22]
    J. Du, Y. Liang, H. Tao, Y. Xu, L. Zhu, and H. Ding, “Load sharing in distributed collaborative manipulation,” IEEE Robot. Autom. Lett., vol. 10, no. 4, pp. 3390–3397, Apr. 2025. doi: 10.1109/LRA.2025.3541924
    [23]
    H.-T. Zhang, H. Xu, B. Xu, Y. Wu, J. Huang, and Q.-L. Han, “Adaptive learning-based distributed control of cooperative robot arm manipulation for unknown objects,” IEEE Trans. Syst., Man, Cybern.: Syst., vol. 53, no. 2, pp. 1298–1307, Feb. 2023. doi: 10.1109/TSMC.2022.3197664
    [24]
    Z. Lu, N. Wang, W. Si, and C. Yang, “Distributed observer-based prescribed performance control for multi-robot deformable object cooperative teleoperation,” IEEE Trans. Autom. Sci. Eng., vol. 21, no. 3, pp. 4143–4154, Jul. 2024. doi: 10.1109/TASE.2023.3292553
    [25]
    A. Marino, “Distributed adaptive control of networked cooperative mobile manipulators,” IEEE Trans. Control Syst. Technol., vol. 26, no. 5, pp. 1646–1660, Sep. 2018. doi: 10.1109/TCST.2017.2720673
    [26]
    D. Zeng, Y. Wang, Y. Jiang, H. Tan, Z. Miao, and Y. Feng, “Distributed neural adaptive impedance control for cooperative manipulation with unknown objects,” IEEE Trans. Neural Netw. Learn. Syst., vol. 36, no. 7, pp. 12363–12376, Jul. 2025. doi: 10.1109/TNNLS.2024.3478215
    [27]
    T. Xu, T. Yang, Z. Duan, G. Feng, and G. Chen, “Distributed coordination of networked manipulators: A two-layer control scheme,” IEEE Trans. Control Syst. Technol., vol. 31, no. 6, pp. 2660–2672, Nov. 2023. doi: 10.1109/TCST.2023.3277595
    [28]
    Y. Song, Y. Wang, J. Holloway, and M. Krstic, “Time-varying feedback for regulation of normal-form nonlinear systems in prescribed finite time,” Automatica, vol. 83, pp. 243–251, Sep. 2017. doi: 10.1016/j.automatica.2017.06.008
    [29]
    H. Ye and Y. Song, “Prescribed-time tracking control of MIMO nonlinear systems with nonvanishing uncertainties,” IEEE Trans. Autom. Control, vol. 68, no. 6, pp. 3664–3671, Jun. 2023. doi: 10.1109/TAC.2022.3194100
    [30]
    Y. Cao, J. Cao, and Y. Song, “Practical prescribed time control of euler-lagrange systems with partial/full state constraints: A settling time regulator-based approach,” IEEE Trans. Cybern., vol. 52, no. 12, pp. 13096–13105, Dec. 2022. doi: 10.1109/TCYB.2021.3100764
    [31]
    Z. Wang, H.-K. Lam, Y. Guo, B. Xiao, Y. Li, X. Su, E. M. Yeatman, and E. Burdet, “Adaptive event-triggered control for nonlinear systems with asymmetric state constraints: A prescribed-time approach,” IEEE Trans. Autom. Control, vol. 68, no. 6, pp. 3625–3632, Jun. 2023. doi: 10.1109/TAC.2022.3194880
    [32]
    A.-M. Zou, Y. Liu, Z.-G. Hou, and Z. Hu, “Practical predefined-time output-feedback consensus tracking control for multiagent systems,” IEEE Trans. Cybern., vol. 53, no. 8, pp. 5311–5322, Aug. 2023. doi: 10.1109/TCYB.2022.3207325
    [33]
    Y. Yao, Y. Kang, Y. Zhao, P. Li, and J. Tan, “A novel prescribed-time control approach of state-constrained high-order nonlinear systems,” IEEE Trans. Syst., Man, Cybern.: Syst., vol. 54, no. 5, pp. 2941–2951, May 2024. doi: 10.1109/TSMC.2024.3352905
    [34]
    Y. Zhang, K. Pang, J. Zhou, Y. Yang, and C. Hua, “Fixed-time composite learning control of robots with prescribed time error constraints,” IEEE/ASME Trans. Mechatronics, vol. 30, no. 1, pp. 426–435, Feb. 2025. doi: 10.1109/TMECH.2024.3400980
    [35]
    Z. Zhang, Y. Dong, and G. Duan, “Global asymptotic fault-tolerant tracking for time-varying nonlinear complex systems with prescribed performance,” Automatica, vol. 159, Art. no. 111345, Jan. 2024.
    [36]
    K. Xia, X. Li, K. Li, and Y. Zou, “Distributed predefined-time control for cooperative tracking of multiple quadrotor UAVs,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 10, pp. 2179–2181, Oct. 2024. doi: 10.1109/JAS.2023.123861
    [37]
    X. Zhao, Y. Song, and H. Ye, “Adaptive distributed event-triggered cooperative manipulation of multiple manipulators under partial time-interval error constraints,” IEEE Trans. Syst., Man, Cybern.: Syst., vol. 55, no. 12, pp. 9309–9323, Dec. 2025. doi: 10.1109/TSMC.2025.3616150
    [38]
    P. Yang, Y. Su, and L. Zhang, “Proximate fixed-time fault-tolerant tracking control for robot manipulators with prescribed performance,” Automatica, vol. 157, Art. no. 111262, Nov. 2023.
    [39]
    Y. Wang, G. Zong, X. Zhao, and Y. Yi, “Adaptive practical fixed-time synchronized tracking control of ASV with prescribed performance,” Automatica, vol. 166, Art. no. 111716, Aug. 2024.
    [40]
    C. Godsil and G. Royle, Algebraic Graph Theory. New York, USA: Springer, 2001.
    [41]
    S. E. Parsegov, A. E. Polyakov, and P. S. Shcherbakov, “Fixed-time consensus algorithm for multi-agent systems with integrator dynamics,” IFAC Proc. Vol., vol. 46, no. 27, pp. 110–115, Sep. 2013. doi: 10.3182/20130925-2-DE-4044.00055
    [42]
    F. Wang, B. Chen, C. Lin, and X. Li, “Distributed adaptive neural control for stochastic nonlinear multiagent systems,” IEEE Trans. Cybern., vol. 47, no. 7, pp. 1795–1803, Jul. 2017. doi: 10.1109/TCYB.2016.2623898
    [43]
    Y. Orlov, “Time space deformation approach to prescribed-time stabilization: Synergy of time-varying and non-Lipschitz feedback designs,” Automatica, vol. 144, Art. no. 110485, Oct. 2022.
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