Studies on system engineering—III optimal choice of the balance measurements in complicated chemical engineering systems

Václavek, V.

doi:10.1016/0009-2509(69)87003-x

Cited by 63 publications

(24 citation statements)

References 2 publications

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“…The first publications relate to the linear systems. Vaclavek [1] was the first to classify the variables in observable and no observable variables. Mah [2] proposed an algorithm of observability based on the graph theory; on the other hand, Crowe [3] gave a classificationi of the variables starting from a matrix of projection.…”

Section: Introductionmentioning

confidence: 99%

Observability and reliability of a photovoltaic sensor

Bennouna

Héraud

Cristofari

2004

2004 IEEE International Symposium on Industrial Electronics

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Section: Introductionmentioning

confidence: 99%

Observability and reliability of a photovoltaic sensor

Bennouna

Héraud

Cristofari

2004

2004 IEEE International Symposium on Industrial Electronics

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“…Previous work concerning fault tolerance with respect to sensor failures in static linear systems was stemmed from [1]. Graph theory based algorithms and a classification of the system variables have been proposed in [1,2,3].…”

Section: Introditctionmentioning

confidence: 99%

An efficient algorithm for intelligent instrumentation system

Hoblos

Chafouk

Langlois

2004

2004 IEEE International Symposium on Industrial Electronics

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The reconfiguration of sensor svstems to solve estimation or control problem is one of the most important tasks in the design of process instrumentation. This paper proposes an algorithm, which guarantees the availability of all state variables even in the case of lost sensors. The v-ariable observabilitv is considered to be necessary for the process supervision of the svstem. Minimal and redundant sensor sets are organized into an oriented graph, which contains all the possible reconfiguration paths for which those variables remain observable. Based on redundancv degrees criteria, an optimal reconfiguration will be used to observe and reconstruct lost information. An example illustrates the proposed algorithm.

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“…For single-component flow networks, networks with linear constraints, or mass-energy flow networks, efficient classification algorithms already exist (Vaclavek, 1969;Mah et al, 1976;Stanley and Mah, 1981b;Crowe et al, 1983). In this paper we extend the treatment to multicomponent flow networks, but exclude energy balances and chemical reactions from our present consideration.…”

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confidence: 99%