Arbitrary Time Spherical Synchronization of a Class of Uncertain Nonlinear Systems via Adaptive Control

ABSTRACT This paper addresses the arbitrary time spherical synchronization problem for a class of uncertain nonlinear systems. Firstly, a novel synchronization paradigm, termed spherical synchronization, is introduced. This paradigm requires the state trajectory of the response system to converge and remain on a hypersphere centered on the state trajectory of the drive system with a prescribed radius . It is crucial that when , this mechanism fundamentally eliminates the collision risk inherent in traditional synchronization scheme (e.g., guaranteeing a minimum safety distance in the unmanned aerial vehicle formations). Secondly, a new sufficient criterion for arbitrary‐time stability is proposed. This criterion is deliberately constructed without exponential terms (e.g., ), significantly reducing computational complexity and enhancing its applicability in controlling nonlinear systems. Thirdly, utilizing this novel stability criterion and adaptive control techniques, sufficient conditions for achieving spherical synchronization in the target class of uncertain nonlinear systems are derived. Finally, the effectiveness and feasibility of the proposed approach are demonstrated through numerical simulations based on a new financial system. Simulation results conclusively validate the performance of the method.

Authors

Institutions

Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2026-03-15
DOI
https://doi.org/10.1002/rnc.70514
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Arbitrary Time Spherical Synchronization of a Class of Uncertain Nonlinear Systems via Adaptive Control

Luxia Han, Jiacheng Li, ZiKang Meng, Runzi Luo
International Journal of Robust and Nonlinear Control
Distributed Control Multi-Agent Systems
article

Arbitrary Time Spherical Synchronization of a Class of Uncertain Nonlinear Systems via Adaptive Control

Luxia Han, Jiacheng Li, ZiKang Meng, Runzi Luo
article en

Abstract

ABSTRACT This paper addresses the arbitrary time spherical synchronization problem for a class of uncertain nonlinear systems. Firstly, a novel synchronization paradigm, termed spherical synchronization, is introduced. This paradigm requires the state trajectory of the response system to converge and remain on a hypersphere centered on the state trajectory of the drive system with a prescribed radius . It is crucial that when , this mechanism fundamentally eliminates the collision risk inherent in traditional synchronization scheme (e.g., guaranteeing a minimum safety distance in the unmanned aerial vehicle formations). Secondly, a new sufficient criterion for arbitrary‐time stability is proposed. This criterion is deliberately constructed without exponential terms (e.g., ), significantly reducing computational complexity and enhancing its applicability in controlling nonlinear systems. Thirdly, utilizing this novel stability criterion and adaptive control techniques, sufficient conditions for achieving spherical synchronization in the target class of uncertain nonlinear systems are derived. Finally, the effectiveness and feasibility of the proposed approach are demonstrated through numerical simulations based on a new financial system. Simulation results conclusively validate the performance of the method.

International Journal of Robust and Nonlinear Control
Nanchang University (CN)
Openalex Percentile: Top 24%
Distributed Control Multi-Agent Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.