Abstract
This article considers the practical fixed-time control algorithm of multi-agent systems (MASs) with unmeasurable states and disturbances. Neural networks are introduced to fit the nonlinear functions of MASs due to the existence of unknown dynamics. The unmeasured states and unknown disturbances in MASs are estimated by applying the extended state observer (ESO). The adding power integration method is combined with the backstepping approach, which avoids the singular phenomenon in the fixed time controller. Besides, the command filter is used in the standard backstepping approach, reducing the computational complexity in the controller design. On the basis of the practical fixed-time stability theory, it is guaranteed that the tracking error of MASs converges within a fixed time, and the initial states of MASs do not affect the convergence time. The simulation case verifies the validity of the proposed MASs consensus algorithm.
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This work was funded in part by the National Natural Science Foundation of China grant under number 62006192, in part by the China Postdoctoral Science Foundation under number 2021TQ0269.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by MY, ZW, D-xY, ZW, and Y-JL. All authors read and approved the final manuscript.
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Yang, M., Wang, Z., Yu, D. et al. Extended state observer-based non-singular practical fixed-time adaptive consensus control of nonlinear multi-agent systems. Nonlinear Dyn 111, 10097–10111 (2023). https://doi.org/10.1007/s11071-023-08352-7
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DOI: https://doi.org/10.1007/s11071-023-08352-7