Simultaneous Estimation of State and Packet-Loss Occurrences in Networked Control Systems

TL;DR

This paper proposes two recursive filtering methods for simultaneously estimating plant states and packet loss events in networked control systems, enhancing fault detection and control performance.

Contribution

It introduces novel recursive estimators based on input-output and state-space models for joint estimation of states and packet losses in NCS.

Findings

The proposed methods outperform existing approaches in simulation.

The estimators accurately detect packet losses and estimate states.

Comparative analysis shows improved robustness over interacting multiple model methods.

Abstract

Estimating the occurrence of packet losses in a networked control systems (NCS) can be used to improve the control performance and to detect failures or cyber-attacks. This study considers simultaneous estimation of the plant state and the packet loss occurrences at each time step. After formulation of the problem, two solutions are proposed. In the first one, an input-output representation of the NCS model is used to design a recursive filter for estimation of the packet loss occurrences. This estimation is then used for state estimation through Kalman filtering. In the second solution, a state space model of NCS is used to design an estimator for both the plant state and the packet loss occurrences which employs a Kalman filter. The effectiveness of the solutions is shown during an example and comparisons are made between the proposed solutions and another solution based on the interacting multiple model estimation method.