Representing Causality and Reasoning about Controllability of Multi-level Flow-Systems

Kai Heussen; Morten Lind

doi:10.1109/ICSMC.2010.5642272

Representing Causality and Reasoning about Controllability of Multi-level Flow-Systems

Kai Heussen, Morten Lind

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Safe operation of complex processes requires that operators maintain situational-awareness even in highly automated environments. Automatic reasoning can support operators as well as the automation system itself to react effectively and appropriately to disturbances. However, knowledge-based reasoning about control situations remains a challenge due to the entanglement of process and control systems that co-establish the intended causal structure of a process. Due to this entanglement, reasoning about such systems depends on a coherent representation of control and process. This paper explains modeling of controlled processes with multilevelflow models and proposes a new framework for modeling causal influence in multilevel flow models on the basis of a flow/potential analogy. The results are illustrated on examples from the domain of electric power systems.

Original language	English
Title of host publication	2010 IEEE International Conference on Systems, Man, and Cybernetics : Intelligent Systems for a Safe and Secure World
Publisher	IEEE
Publication date	2010
ISBN (Print)	978-1-4244-6586-6
DOIs	https://doi.org/10.1109/ICSMC.2010.5642272
Publication status	Published - 2010
Event	IEEE International Conference on Systems, Man, and Cybernetics : Intelligent Systems for a Safe and Secure World - Istanbul Duration: 1 Jan 2010 → …

Conference

Conference	IEEE International Conference on Systems, Man, and Cybernetics : Intelligent Systems for a Safe and Secure World
City	Istanbul
Period	01/01/2010 → …

Bibliographical note

Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Keywords

Causality
Knowledge-based Systems
Functional Modeling
Model-based reasoning
Power Systems
Intelligent Control
Means-ends

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10.1109/ICSMC.2010.5642272

Smc2010Submitted manuscript, 1.92 MB

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Cite this

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title = "Representing Causality and Reasoning about Controllability of Multi-level Flow-Systems",

abstract = "Safe operation of complex processes requires that operators maintain situational-awareness even in highly automated environments. Automatic reasoning can support operators as well as the automation system itself to react effectively and appropriately to disturbances. However, knowledge-based reasoning about control situations remains a challenge due to the entanglement of process and control systems that co-establish the intended causal structure of a process. Due to this entanglement, reasoning about such systems depends on a coherent representation of control and process. This paper explains modeling of controlled processes with multilevelflow models and proposes a new framework for modeling causal influence in multilevel flow models on the basis of a flow/potential analogy. The results are illustrated on examples from the domain of electric power systems.",

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Heussen, K & Lind, M 2010, Representing Causality and Reasoning about Controllability of Multi-level Flow-Systems. in 2010 IEEE International Conference on Systems, Man, and Cybernetics: Intelligent Systems for a Safe and Secure World. IEEE, IEEE International Conference on Systems, Man, and Cybernetics : Intelligent Systems for a Safe and Secure World, Istanbul, 01/01/2010. https://doi.org/10.1109/ICSMC.2010.5642272

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N1 - Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2010

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N2 - Safe operation of complex processes requires that operators maintain situational-awareness even in highly automated environments. Automatic reasoning can support operators as well as the automation system itself to react effectively and appropriately to disturbances. However, knowledge-based reasoning about control situations remains a challenge due to the entanglement of process and control systems that co-establish the intended causal structure of a process. Due to this entanglement, reasoning about such systems depends on a coherent representation of control and process. This paper explains modeling of controlled processes with multilevelflow models and proposes a new framework for modeling causal influence in multilevel flow models on the basis of a flow/potential analogy. The results are illustrated on examples from the domain of electric power systems.

AB - Safe operation of complex processes requires that operators maintain situational-awareness even in highly automated environments. Automatic reasoning can support operators as well as the automation system itself to react effectively and appropriately to disturbances. However, knowledge-based reasoning about control situations remains a challenge due to the entanglement of process and control systems that co-establish the intended causal structure of a process. Due to this entanglement, reasoning about such systems depends on a coherent representation of control and process. This paper explains modeling of controlled processes with multilevelflow models and proposes a new framework for modeling causal influence in multilevel flow models on the basis of a flow/potential analogy. The results are illustrated on examples from the domain of electric power systems.

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