Resilient algorithm for distributed resource allocation under false data injection attacks
For a first‐order nonlinear multi‐agent system who is subject to false data injection (FDI) attacks on agents' actuators and sensors, agents execute a distributed resource allocation algorithm according to the compromised control inputs and interactive information such that the multi‐agent syst...
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| Vydané v: | Asian journal of control Ročník 26; číslo 4; s. 1635 - 1645 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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01.07.2024
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| ISSN: | 1561-8625, 1934-6093 |
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| Abstract | For a first‐order nonlinear multi‐agent system who is subject to false data injection (FDI) attacks on agents' actuators and sensors, agents execute a distributed resource allocation algorithm according to the compromised control inputs and interactive information such that the multi‐agent system is unstable and agents' decisions deviate from the optimal resource allocation. At first, we analyze the robustness of the distributed resource allocation algorithm under the FDI attacks. Then, a resilient distributed algorithm is proposed to solve the distributed resource allocation problem by resisting the adverse effect of the attacks. In detail, the unknown nonlinear term and the false data injected in agents are considered as extended states that can be estimated by extended state observers. The estimation is used in the feedback control to suppress the effect of the FDI attacks. As a result, the designed resilient algorithm ensures that agents' decisions converge to the optimal allocation without requiring any information about the nature of the attacks. An example is given to illustrate the results. |
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| AbstractList | For a first‐order nonlinear multi‐agent system who is subject to false data injection (FDI) attacks on agents' actuators and sensors, agents execute a distributed resource allocation algorithm according to the compromised control inputs and interactive information such that the multi‐agent system is unstable and agents' decisions deviate from the optimal resource allocation. At first, we analyze the robustness of the distributed resource allocation algorithm under the FDI attacks. Then, a resilient distributed algorithm is proposed to solve the distributed resource allocation problem by resisting the adverse effect of the attacks. In detail, the unknown nonlinear term and the false data injected in agents are considered as extended states that can be estimated by extended state observers. The estimation is used in the feedback control to suppress the effect of the FDI attacks. As a result, the designed resilient algorithm ensures that agents' decisions converge to the optimal allocation without requiring any information about the nature of the attacks. An example is given to illustrate the results. |
| Author | Nan, Xinyuan Chen, Xingzhi Gao, Bingpeng Cai, Xin |
| Author_xml | – sequence: 1 givenname: Xingzhi surname: Chen fullname: Chen, Xingzhi organization: Xinjiang University – sequence: 2 givenname: Xin orcidid: 0000-0001-5899-574X surname: Cai fullname: Cai, Xin email: xincai@xju.edu.cn organization: Xinjiang University – sequence: 3 givenname: Bingpeng surname: Gao fullname: Gao, Bingpeng organization: Xinjiang University – sequence: 4 givenname: Xinyuan surname: Nan fullname: Nan, Xinyuan organization: Xinjiang University |
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| SubjectTerms | Actuators Algorithms Decisions distributed algorithm false data injection attacks Feedback control Interactive control Interactive systems Nonlinear control nonlinear dynamics resilient algorithm Resource allocation State observers |
| Title | Resilient algorithm for distributed resource allocation under false data injection attacks |
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