Distributed Secure State Estimation in the Presence of Malicious Agents

• 成果类型: Article
• 署名作者: Lu, An-Yang; Yang, Guang-Hong
• 署名单位: Northeastern University - China; Northeastern University - China
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3010769
• 发表日期: 2021
• 页码: 2875-2882
• 关键词: State estimation; optimization; resilience; switches; reliability; sensors; distributed optimization; distributed secure state estimation; distributed system; gradient descent algorithm; malicious agents

摘要

This article investigates the distributed secure state estimation problem of distributed systems where a set of agents estimates the state cooperatively in the presence of malicious agents. First, a sufficient condition for the solvability of the distributed secure state estimation problem is proposed. Second, based on the obtained condition, a distributed switched gradient descent (DSGD) algorithm is designed to solve the considered problem which is transformed into a distributed optimization problem. With the help of a candidate-removal mechanism, the proposed DSGD algorithm successfully generates reliable state estimates despite malicious agents. Finally, the effectiveness of the proposed algorithm is illustrated by a numerical example.