Minimum-Time and Minimum-Triggering Observability of Stochastic Boolean Networks

This article investigates the observability of Markovian jump Boolean networks (MJBNs) via algebraic state space representation approach. A necessary and sufficient criterion in the form of linear programming is derived for the asymptotic observability in distribution of MJBNs, and several conditions are obtained for the finite-time observability based on the properties of nilpotent matrices. Subsequently, in order to minimize the time consumption, a maximum principle is established to address the minimum-time observability problem. With regard to the event-triggered output feedback observability, an efficient procedure is developed to minimize the number of triggering events. Finally, three numerical examples are employed to demonstrate the effectiveness of theoretical results.