Stephen A, Karthikeyan R, Sowmiya C, Raja R, Agarwal Ravi P
Center for Computational Modeling, Chennai Institute of Technology, Chennai 600 069, India; School of Information and Control Engineering, Kunsan National University, Gunsan-siJeonbuk The Republic of Korea.
Center for Nonlinear Systems, Chennai Institute of Technology, Chennai, India.
Neural Netw. 2024 Feb;170:506-520. doi: 10.1016/j.neunet.2023.11.059. Epub 2023 Nov 30.
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.
本研究的目的是研究具有状态量化和时变延迟的多智能体系统（MASs）在采样数据控制方法下的同步准则。目前，已经开发了一种循环Lyapunov-Krasovskii泛函（LKF），它整合了采样间隔的信息，以确保领导者系统与跟随者系统同步，从而得到线性矩阵不等式（LMI）形式的特定条件。使用Matlab中的LMI控制工具箱可以轻松求解这些LMI。最后，通过数值模拟和比较结果证明了所提方法的可行性和有效性。
