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Distributed Secure State Estimation in the Presence of Malicious Agents

An‐Yang Lu, Guang‐Hong Yang

2020IEEE Transactions on Automatic Control27 citationsDOI

Abstract

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.

Topics & Concepts

State (computer science)Computer scienceGradient descentDistributed algorithmSet (abstract data type)Mathematical optimizationEstimationDistributed computingAlgorithmMathematicsArtificial intelligenceEngineeringArtificial neural networkSystems engineeringProgramming languageDistributed Control Multi-Agent SystemsStability and Control of Uncertain SystemsNeural Networks Stability and Synchronization
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