On an Optimization Problem in Sensor Selection
Discrete Event Dynamic Systems
Active Acquisition of Information for Diagnosis and Supervisory Control of Discrete Event Systems
Discrete Event Dynamic Systems
On the Minimization of Communication in Networked Systems with a Central Station
Discrete Event Dynamic Systems
Energy Minimization for Flat Routing and Hierarchical Routing for Wireless Sensor Networks
SENSORCOMM '08 Proceedings of the 2008 Second International Conference on Sensor Technologies and Applications
Fault Diagnosis with Static and Dynamic Observers
Fundamenta Informaticae - Application of Concurrency to System Design, the Sixth Special Issue
Dynamic sensor activation for event diagnosis
ACC'09 Proceedings of the 2009 conference on American Control Conference
A Sampling Theorem Approach to Traffic Sensor Optimization
IEEE Transactions on Intelligent Transportation Systems
| Hi-index | 22.14 |
The problem of dynamic sensor activation for event diagnosis in partially observed discrete event systems is considered. Diagnostic agents are able to activate sensors dynamically during the evolution of the system. Sensor activation policies for diagnostic agents are functions that determine which sensors are to be activated after the occurrence of a trace of events. The sensor activation policy must satisfy the property of diagnosability of centralized systems or codiagnosability of decentralized systems. A policy is said to be minimal if there is no other policy, with strictly less sensor activation, that achieves diagnosability or codiagnosability. To compute minimal policies, we propose language partition methods that lead to efficient computational algorithms. Specifically, we define ''window-based'' language partitions for scalable algorithms to compute minimal policies. By refining partitions, one is able to refine the solution space over which minimal solutions are computed at the expense of more computation. Thus a compromise can be achieved between fineness of solution and complexity of computation.