Resumen de A general approach for optimizing dynamic sensor activation for discrete event systems
We study the problem of dynamic sensor activation for centralized partially-observed discrete event systems. The sensors can be turned on/off online dynamically according to a sensor activation policy in order to satisfy some observation property. We consider a general class of properties, called Information-State-based (or IS-based) properties, which include, but are not limited to, observability, K-diagnosability, predictability, and opacity. We define a new Most Permissive Observer (MPO) that generalizes previous versions of this structure. Based on the generalized MPO, we first synthesize a logical minimal or maximal sensor activation policy based on a set inclusion criterion. Then we study the synthesis of optimal solutions for a given quantitative objective function that considers numerical activation costs and switching costs. Our results generalize previous works on dynamic sensor activation for enforcement of specific properties.
