Diagnosability Analysis of a Class of Hierarchical State Machines
Discrete Event Dynamic Systems
Discrete Event Dynamic Systems
Sequential window diagnoser for discrete-event systems under unreliable observations
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Active fault tolerant control of discrete event systems using online diagnostics
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
A theoretical framework and its practical implications for formulating and implementing model-based monitoring of discrete flow networks are discussed. Possible flows of items are described as discrete-event (DE) traces. Each trace defines the DE sequence(s) that are triggered when an entity follows a given flow-path, visiting tracking locations within the monitored system. To deal with alternative routing, creation of items, flow bifurcations and convergences are allowed. Given the set of possible discrete flows, a possible-behavior model-an interacting set of automata-is constructed, where each automation models the item discrete flow at each tracking location. In this model, which assumes total observability, event labels or symbols contain all the information required to unambiguously distinguish each discrete movement. Within the possible behavior, there is a special sub-behavior whose occurrence is required to be detected. The special behavior may be specified by the occurrence of routing events, such as faults or route violations, for example. These intermittent or non-persistent events may occur repeatedly. An observation mask is then defined, characterizing the observation configuration available for collecting item tracking data. The verification task is to determine whether this observation configuration is capable of detecting the specified special behavior. The assessment is accomplished by evaluating several observability notions, such as detectability and diagnosibility. If the corresponding property is satisfied, associated formal observers are constructed to perform the monitoring task at hand. The synthesis of observation masks may also be conducted to suggest optimal observation configurations (specifying number, type, and tracking locations of observation devices) guaranteeing the detection of special events and to construct associated monitoring agents. The developed framework, modeling methodology, and supporting techniques for defining and implementing discrete flow monitoring of entity movements are presented and illustrated with examples.