State Estimation of Discrete-Event Systems Subject to Intermittent and Permanent Loss of Observations
Yin Tong, Jiate Luo, Carla Seatzu · 2021 60th IEEE Conference on Decision and Control (CDC) · 2021
The state estimation problem in discrete-event systems (DESs) consists in determining the set of states consistent with the observations. Due to sensor malfunction, the occurrence of some events may become unobservable. Moreover, such loss of observations may be intermittent or permanent. In this paper, we study the state estimation problem of discrete-event systems subject to both intermittent and permanent loss of observations. We assume that both types of observation loss are not recoverable. For each event subject to a permanent loss of observation, we propose an automaton model to describe this kind of malfunction. We show that the automaton model describing the behavior of the system in the presence of observation loss can be obtained through the parallel composition of the above automata and an automaton that is obtained with appropriate changes to keep into account observation loss. Finally, the state estimation problem can be solved by constructing the observer of the new model.