Language-based minimization of sensor activation for event diagnosis

The problem of dynamic sensor activation for event diagnosis in discrete event systems is considered. Diagnostic agents are able to activate/deactivate sensors dynamically during the operation of the system. Sensor activation policies are functions that determine which sensors are on after a system trajectory. The sensor activation policy must be sufficient to fulfill the diagnosis duty. To compute minimal policies, in previous work, we propose language partition methods to restrict the solution space to be finite. In this paper, we present an algorithm that can be used to compute a provable minimal sensor activation policy without such a restriction. The output of our algorithm, which is a deterministic finite-state automaton, can be directly used to control sensors and diagnose the system.