Optimal sensor choice for observability in free-choice Petri nets

Aguirre-Salas, L.; Begovich, O.; Ramírez-Treviño, A.

doi:10.1109/isic.2001.971520

Cited by 8 publications

(8 citation statements)

References 6 publications

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“…Note that (16) is solved by searching through s ∈ U \ S cur . Furthermore, (17) means that sensors costing more than ct * are not considered. This criterion is based on the instantaneous performance improvement of the candidate sensor and is myopic.…”

Section: A Motivationmentioning

confidence: 99%

“…Other work on optimal senor selection for DEDS includes [15], [17]- [20]. While [15] addresses computational issues regarding sensor selection for DEDS modeled as finite automata, [17], [18] considers optimal sensor selection for satisfying observability properties in Petri nets.…”

Section: Introductionmentioning

confidence: 99%

“…While [15] addresses computational issues regarding sensor selection for DEDS modeled as finite automata, [17], [18] considers optimal sensor selection for satisfying observability properties in Petri nets. Reference [19] considers the optimization problem in the framework of Fig.…”

Section: Introductionmentioning

confidence: 99%

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Sensor configuration selection for discrete-event systems under unreliable observations

Lin

Yoo

García

2010

2010 IEEE International Conference on Automation Science and Engineering

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Abstract-Algorithms for counting the occurrences of special events in the framework of partially-observed discrete-event dynamical systems (DEDS) were developed in previous work. Their performances typically become better as the sensors providing the observations become more costly or increase in number. This paper addresses the problem of finding a sensor configuration that achieves an optimal balance between cost and the performance of the special event counting algorithm, while satisfying given observability requirements and constraints. Since this problem is generally computational hard in the framework considered, a sensor optimization algorithm is developed using two greedy heuristics, one myopic and the other based on projected performances of candidate sensors. The two heuristics are sequentially executed in order to find best sensor configurations. The developed algorithm is then applied to a sensor optimization problem for a multi-unit-operation system. Results show that improved sensor configurations can be found that may significantly reduce the sensor configuration cost but still yield acceptable performance for counting the occurrences of special events.

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Section: A Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sensor configuration selection for discrete-event systems under unreliable observations

Lin

Yoo

García

2010

2010 IEEE International Conference on Automation Science and Engineering

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“…To characterize structural observability, we generalize the event-detectability property [11], which was originally defined only for unobservable transitions. Notice that there are extreme situations where the Petri net can be structurally observable but never be event-detectable.…”

Section: Definitionmentioning

confidence: 99%

“…In contrast, there is limited previous work on the sensor selection problem when the underlying model is a Petri net. In [11], [12], observability notions are used as criteria when optimizing the selection of sensors in interpreted Petri net (IPN) models [13]. In [12], genetic algorithms are used to approximate the optimal sensor selection, but the main disadvantage is that they converge very slowly to a suboptimal solution.…”

Section: Introductionmentioning

confidence: 99%

Approximating optimal place sensor selection for structural observability in discrete event systems modeled by Petri Nets

Hadjicostis

2007

2007 46th IEEE Conference on Decision and Control

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In this paper, we study place sensor selection problems in Discrete Event Systems modeled by Petri nets with outputs (i.e., Petri nets with transition and place sensors). Our goal is to place a minimal number of sensors so as to maintain the property of structural observability, i.e., the ability to uniquely determine the system state based on sensor information (and knowledge of the system model and initial state). The place sensor selection problem has been shown to be N P-complete and this paper proposes two efficient algorithms to approximate its solution. Simulations suggest that the two methods run faster and can find reasonably good solutions compared to methods that are based on linear integer programming solvers.

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A diagnoser algorithm for anomaly detection in DEDS under partial and unreliable observations: characterization and inclusion in sensor configuration optimization

Lin

García

Yoo

2012

Discrete Event Dyn Syst

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Optimal sensor choice for observability in free-choice Petri nets

Cited by 8 publications

References 6 publications

Sensor configuration selection for discrete-event systems under unreliable observations

Sensor configuration selection for discrete-event systems under unreliable observations

Approximating optimal place sensor selection for structural observability in discrete event systems modeled by Petri Nets

A diagnoser algorithm for anomaly detection in DEDS under partial and unreliable observations: characterization and inclusion in sensor configuration optimization

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