| Project/Area Number |
20K23328
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Multi-year Fund |
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| Review Section |
1001:Information science, computer engineering, and related fields
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| Research Institution | Hiroshima University |
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Principal Investigator |
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| Project Period (FY) |
2020-09-11 – 2023-03-31
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| Project Status |
Discontinued (Fiscal Year 2022)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 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-Agent Systems / Consensus Control / Lyapunov theory |
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| Outline of Research at the Start |
Various consensus control schemes for networked multi-agent systems will be established via Lyapunov-Krasovskii functional and linear matrix inequality approaches. To show the usefulness of consensus scheme, real-life engineering problems to be considered such as Multi-teleoperator systems and so on.
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| Outline of Annual Research Achievements |
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.
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