Active Acquisition of Information for Diagnosis and Supervisory Control of Discrete Event Systems

This paper considers the problems of fault diagnosis and supervisory control in discrete event systems through the context of a new observation paradigm. For events that are considered observable, a cost is incurred each time a sensor is activated in an attempt to make an event observation. In such a situation the best strategy is to perform an “active acquisition” of information, i.e. to choose which sensors need to be activated based on the information state generated from the previous readings of the system. Depending on the sample path executed by the system, different sensors may be turned on or off at different stages of the process. We consider the active acquisition of information problem for both logical and stochastic discrete event systems. We consider three classes of increasing complexity: firstly, for acyclic systems where events are synchronized to clock ticks; secondly, for acyclic untimed systems; and lastly, for general cyclic automata. For each of these cases we define a notion of information state for the problem, determine conditions for the existence of an optimal policy, and construct a dynamic program to find an optimal policy where one exists. For large systems, a limited lookahead algorithm for computational savings is proposed.