Distributed Adaptive Tracking of Random High-Order Nonlinear Multi-Agent Systems with Heterogeneous Powers_Vol. 4 No. 3 (JBDC 2026)_Journal of Big Data and Computing (ISSN: 2959-0590)

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Distributed Adaptive Tracking of Random High-Order Nonlinear Multi-Agent Systems with Heterogeneous Powers

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DOI: https://doi.org/10.62517/jbdc.202601327

Author(s)

Xiaojuan Gong*

Affiliation(s)

School of General Education, Yantai Institute of Science and Technology, Yantai, Shandong, China *Corresponding Author

Abstract

This paper studies distributed adaptive tracking for random high-order nonlinear multi-agent systems whose integrator powers may differ across agents and backstepping stages. The powers are known odd rational numbers, whereas a common drift parameter is unknown and the systems are driven by second-order-moment disturbances. A weighted-degree backstepping construction is developed by using the largest network power to close all recursive estimates within one Lyapunov function. The associated tuning function is derived from the coefficient of the parameter-estimation error, and a leakage term prevents parameter drift. For a pinned undirected communication graph, the resulting closed loop is noise-to-state practically stable in the mean-square sense and an explicit ultimate tracking-error bound is obtained. The same recursion yields a containment extension in which the graph determines the convex-combination weights. Two heterogeneous-power examples illustrate the single- and multiple-leader results. The analysis is limited to full-state feedback, fixed topology, known powers, and bounded second moments; no claim of hardware validation is made.

Keywords

Multi-Agent Systems; Heterogeneous Powers; Random Nonlinear Systems; Adaptive Backstepping; Practical Mean-Square Stability

References

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