Distributed consensus‐based estimation for non‐linear systems subject to missing measurements and Denial of Service attacks

Abstract

Abstract This article studies a distributed consensus‐based estimation problem for discrete time‐varying non‐linear systems with missing measurements and Denial of Service (DoS) attacks. The probability of missing measurements is independent for each sensor. The communication link between sensor nodes is unreliable and subjected to DoS attacks. To achieve accurate state estimation against missing measurements, a local estimator with compensation mechanism is designed for each sensor node. A stochastic event‐triggered mechanism is used to lessen additional information transfer. Based on this, a distributed consensus‐based estimator is constructed by continually fusing local neighbours information matrixs and vectors. Moreover, the analysis of the designed estimator boundedness is presented. Finally, the effectiveness of the proposed algorithm is verified by three numerical examples.

Keywords

• non‐linear control systems
• sensor fusion
• state estimation
• extended Kalman filter