Dynamic sensor activation for event diagnosis

We consider the problem of dynamic sensor activation for event diagnosis in partially-observed discrete-event systems. The observing agent is able to activate sensors dynamically during the evolution of the system. The sensor activation policy is the function that describes which sensors are to be activated after an observed string of events. The sensor activation policy must achieve the requirements of the property of diagnosability previously defined for discrete event systems. A policy is said to be minimal if there is no other policy, with strictly less sensor activation, that achieves diagnosability. For the purpose of computing minimal policies, we define language partition methods that lead to efficient computational algorithms. Specifically, we define ldquowindow-basedrdquo language partitions that lead to scalable algorithms for computing minimal policies. By increasing the size of the window in this class of partitions, one is able to refine the solution space over which minimal solutions are computed.