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Application of Dependency Structure Matrices and Multilevel Synthesis to a Production Line

The work

AuthorsFerdie F. H. Reijnen; Martijn A. Goorden; Joanna M. van de Mortel-Fronczak; Michel A. Reniers; J.E. Rooda
Editors
Typemisc
Year2018
Citekeyreijnen2018application

Where it appeared

Published inIEEE Conference on Control Technology and Applications (CCTA)
Pages458--464

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Abstract

Designing correct supervisory controllers for high-tech systems is becoming increasingly complex due to demands for verified safety, higher quality, and more functionality. Based on supervisory control theory, a method is defined to automatically derive a supervisor from a model of the uncontrolled system (the plant) and a model of the control requirements. A drawback of this approach is the computational complexity that grows exponentially with the number of components in the system. Several control architectures have been proposed in the literature to overcome this problem. It is not always evident which control architecture is most suitable for a given system. Therefore, the research on methods supporting automatic architecture generation gains in importance. The purpose of this paper is to illustrate such a method in a case study involving the development of supervisory control. The control architecture is automatically derived from the plant and requirement models, using clustering techniques for dependency structure matrices. The following development steps are discussed: modeling the plant, modeling the requirements, structuring the models in a multilevel control architecture, synthesizing the supervisors, and generating a real-time controller for implementation.

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Cite it as

@misc{reijnen2018application,
  title        = {Application of Dependency Structure Matrices and Multilevel Synthesis to a Production Line},
  author       = {Ferdie F. H. Reijnen and Martijn A. Goorden and Joanna M. van de Mortel-Fronczak and Michel A. Reniers and J.E. Rooda},
  year         = {2018},
  journal      = {IEEE Conference on Control Technology and Applications (CCTA)},
  pages        = {458--464},
  doi          = {10.1109/ccta.2018.8511449},
}

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