Sampled-data controller scheme for multi-agent systems and its Application to circuit network

The objective of this study is to investigate the synchronization criteria under the sampled-data control method for multi-agent systems (MASs) with state quantization and time-varying delay. Currently, a looped Lyapunov–Krasovskii Functional (LKF) has been developed, which integrates information fr...

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Bibliographic Details
Published in:Neural networks 2024-02, Vol.170, p.506-520
Main Authors: Stephen, A., Karthikeyan, R., Sowmiya, C., Raja, R., Agarwal, Ravi P.
Format: Article
Language:English
Subjects:
Linear matrix inequality
Looped Lyapunov functional
Multi-agent systems
Neural Networks, Computer
Sampled data
State quantization
Time Factors
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Summary:The objective of this study is to investigate the synchronization criteria under the sampled-data control method for multi-agent systems (MASs) with state quantization and time-varying delay. Currently, a looped Lyapunov–Krasovskii Functional (LKF) has been developed, which integrates information from the sampling interval to ensure that the leader system synchronizes with the follower system, resulting in a specific condition in the form of Linear Matrix Inequalities (LMIs). The LMIs can be easily solved using the LMI Control toolbox in Matlab. Finally, the proposed approach’s feasibility and effectiveness are demonstrated through numerical simulations and comparative results.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2023.11.059