Estimation And Fault Detection of Discrete Event Systems Modeled By Time Interval Petri Nets

Abstract

This work is interested in studying discrete event systems modeled by time interval Petri nets. Indeed, a new state model describing the time evolution of the system is proposed. The simulation of the proposed state model gives the upper and lower bounds of each element of the system state and the system outputs. After that, a new state estimator is proposed allowing estimating the whole system state and inputs. This estimator give, also, an upper and lower bounds for each elements of the state vector and the input. The state model and the estimator are both proposed along, successively, count and dater approaches. For count approach, the system state is the number of transition firing and for dater approach, it is the dates of transitions firing. The proposed state model and estimator are applied to a baking process described by a time interval Petri nets. This application show the robustness of the state and input estimation. The proposed state model and estimator are used also for fault detection, localization and estimation and it is shown that they give acceptable results.