Consensus Control of Networked Multi-Agent Systems and Its Applications

网络化多Agent系统的共识控制及其应用

• 批准号: 20K23328
• 负责人: RAMASAMY SARAVANAKUMAR
• 金额: $ 1.75万
• 依托单位: Hiroshima University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Research Activity Start-up
• 财政年份: 2020
• 资助国家: 日本
• 起止时间: 2020-09-11 至 2023-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20K23328/
• 关键词: Consensus control; Multi-agent systems; Memory sampled-data; Linear matrix inequality; Multi agent systems; Consensus; Looped functional method; Lyapunov stability; Sampled-data control; Sampled-data consensus; Looped-functional method; Multi-A

Consensus-based stabilization studies of multi-agent systems are proposed in this project. In particular, a memory-based sampled-data consensus framework for multi-agent systems in the presence of nonlinear actuator faults is studied. To reduce state exchanges and conserve energy resources, communication between neighboring agents is based solely on state samples at variable sampling intervals. As two general constraints of the actuator, both bounded nonlinear partial loss of effectiveness and bias failure are considered in the problem formulation. Sufficient conditions to guarantee consensus under certain circumstances are derived as linear matrix inequality conditions. Unlike existing Lyapunov-Krasovskii-based methods, the design framework proposed in this brief is based on a loop-functional approach that reduces conservatism in the design of the required consensus control gains. This less conservative approach allows for larger sampling intervals as well as more severe actuator failures, increasing the utility of the proposed approach. To obtain simulation results, the MATLAB Yalmip parser and SDPT3 solver are effectively used in this project. Simulation results based on tunnel diode circuit and a nonholonomic mobile robot MAS quantifies the effectiveness of the proposed approach. Additionally, the gain matrix of the sampled data controller is obtained by solving the inequality of the derived linear matrix. Moreover, robust exponential stability and Takagi-Sugeno fuzzy control synthesis for networked control systems via H∞ performance has been investigated.

本项目提出了基于共识的多智能体系统镇定研究。针对存在非线性执行器故障的多智能体系统，研究了一种基于记忆的采样数据一致性框架。为了减少状态交换和节约能源，相邻代理之间的通信仅基于可变采样间隔的状态样本。作为执行器的两个一般约束，在问题描述中同时考虑了有界非线性部分有效性损失和偏置失效。给出了在一定条件下保证一致的充分条件，即线性矩阵不等式条件。与现有的基于Lyapunov-Krasovskii的方法不同，本简介中提出的设计框架基于回路函数方法，该方法减少了所需共识控制增益设计中的保守性。这种不太保守的方法允许更大的采样间隔以及更严重的执行器故障，从而增加了所提出的方法的实用性。为了得到仿真结果，在本项目中有效地使用了MatLab Yalmip解析器和SDPT3求解器。基于隧道二极管电路和非完整移动机器人MAS的仿真结果量化了该方法的有效性。另外，通过求解得到的线性矩阵的不等式，得到采样数据控制器的增益矩阵。此外，还研究了基于H-∞性能的网络控制系统的鲁棒指数稳定性和高木-杉野模糊控制综合问题。

项目成果

Reliable Memory Sampled-Data Consensus of Multi-Agent Systems With Nonlinear Actuator Faults

具有非线性执行器故障的多智能体系统的可靠内存采样数据一致性

• DOI: 10.1109/tcsii.2021.3124043
• 发表时间: 2022
• 期刊: IEEE Transactions on Circuits and Systems II: Express Briefs
• 作者: Saravanakumar Ramasamy;Amini Amir;Datta Rupak;Cao Yang
• 通讯作者: Cao Yang

Reliable Memory Sampled-Data Control for T–S Fuzzy Systems

• DOI: 10.1016/j.ifacol.2022.04.118
• 发表时间: 2022
• 期刊: IFAC-PapersOnLine
• 作者: Ramasamy Saravanakumar;Kaibo Shi;R. Datta

Further Stability and L2-Gain Conditions for Sampled-Data Systems

采样数据系统的进一步稳定性和 L2 增益条件

• 发表时间: 2021
• 作者: Saravanakumar Ramasamy;Cao Yang;Kazemy Ali;Zhu Quanxin;Saravanakumar Ramasamy;Ramasamy Saravanakumar
• 通讯作者: Ramasamy Saravanakumar

Dissipative Control for Delayed T-S fuzzy System with Data Packet Dropout

具有数据包丢失的延迟T-S模糊系统的耗散控制

• 发表时间: 2021
• 作者: Saravanakumar Ramasamy;Cao Yang;Kazemy Ali;Zhu Quanxin;Saravanakumar Ramasamy;Ramasamy Saravanakumar;Ramasamy Saravanakumar
• 通讯作者: Ramasamy Saravanakumar

Sampled-data based extended dissipative synchronization of stochastic complex dynamical networks

• DOI: 10.3934/dcdss.2022082
• 发表时间: 2022
• 期刊: Discrete & Continuous Dynamical Systems - S
• 作者: Ramasamy Saravanakumar;Yang Cao;A. Kazemy;Quanxin Zhu