A general approach for optimizing dynamic sensor activation for discrete event systems

摘要

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 dass 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. (C) 2019 Elsevier Ltd. All rights reserved.