Distributed Containment Control for Discrete-Time Nonlinear Multiagent Systems Over Dynamic Topology With System Uncertainties

This article explores the distributed containment control problem under dynamic directed topologies in discrete-time nonlinear multiagent systems (MASs) subject to parameter uncertainties that are nonlinearly coupled with the agents' states. Specifically, a parameter estimation algorithm is fir...

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Published in:IEEE systems journal Vol. 19; no. 2; pp. 483 - 494
Main Authors: Du, Changkun, Li, Nannan, Li, Zhen, Yu, Samson Shenglong, Lim, Chee Peng
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Aerodynamics
Containment
Containment control
Control systems
Convergence
Convex hulls
Convexity
directed dynamic topology
Directed graphs
Discrete time systems
discrete-time multiagent systems (MASs)
distributed adaptive control
Graph theory
Markov analysis
Markov chains
Multiagent systems
Nonlinear control
Nonlinear systems
nonlinearity and uncertainty
Parameter estimation
Parameter uncertainty
Protocols
Reference signals
Simulation
Switches
Topology
Uncertainty
Vehicle dynamics
ISSN:1932-8184, 1937-9234
Online Access:Get full text
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Abstract This article explores the distributed containment control problem under dynamic directed topologies in discrete-time nonlinear multiagent systems (MASs) subject to parameter uncertainties that are nonlinearly coupled with the agents' states. Specifically, a parameter estimation algorithm is first adopted to deal with the parametric uncertainty. Then, based on the estimated parameters, a distributed adaptive containment control protocol is proposed in a distributed fashion for nonlinear and uncertain MASs over dynamic digraphs. To tackle the challenges caused by the dynamic topology, the evolution of the dynamic topology of MASs is transformed into time-varying Markov chains. By analyzing the characteristics of time-varying Markov chains, the properties of some key matrices related to the dynamic topology are derived, which benefits the convergence analysis of containment control. By applying the proposed control protocol, the reference signals can be tracked by the leaders, while the followers' states are driven into the convex hull formed by leaders. Finally, simulation results and performance analysis are discussed to demonstrate the effectiveness of developed methods.
AbstractList This article explores the distributed containment control problem under dynamic directed topologies in discrete-time nonlinear multiagent systems (MASs) subject to parameter uncertainties that are nonlinearly coupled with the agents' states. Specifically, a parameter estimation algorithm is first adopted to deal with the parametric uncertainty. Then, based on the estimated parameters, a distributed adaptive containment control protocol is proposed in a distributed fashion for nonlinear and uncertain MASs over dynamic digraphs. To tackle the challenges caused by the dynamic topology, the evolution of the dynamic topology of MASs is transformed into time-varying Markov chains. By analyzing the characteristics of time-varying Markov chains, the properties of some key matrices related to the dynamic topology are derived, which benefits the convergence analysis of containment control. By applying the proposed control protocol, the reference signals can be tracked by the leaders, while the followers' states are driven into the convex hull formed by leaders. Finally, simulation results and performance analysis are discussed to demonstrate the effectiveness of developed methods.
Author Li, Zhen
Du, Changkun
Lim, Chee Peng
Yu, Samson Shenglong
Li, Nannan
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SubjectTerms Aerodynamics
Containment
Containment control
Control systems
Convergence
Convex hulls
Convexity
directed dynamic topology
Directed graphs
Discrete time systems
discrete-time multiagent systems (MASs)
distributed adaptive control
Graph theory
Markov analysis
Markov chains
Multiagent systems
Nonlinear control
Nonlinear systems
nonlinearity and uncertainty
Parameter estimation
Parameter uncertainty
Protocols
Reference signals
Simulation
Switches
Topology
Uncertainty
Vehicle dynamics
Title Distributed Containment Control for Discrete-Time Nonlinear Multiagent Systems Over Dynamic Topology With System Uncertainties
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