DSM-based analysis for the recognition of modeling errors in supervisory controller design

Martijn Goorden; Joanna van de Mortel-Fronczak; Pascal Etman; Jacobus Rooda

doi:10.35199/dsm2019.7

DSM-based analysis for the recognition of modeling errors in supervisory controller design

Control Systems Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

3 Citations (Scopus)

1 Downloads (Pure)

Abstract

The design of supervisory controllers for cyber-physical systems is steadily becoming harder as increasingly more functionality needs to be automated, the systems become larger, and safe operation becomes more important. Model-based systems engineering incorporating formal methods such as supervisory control synthesis can be used to synthesize these supervisory controllers based on models of the uncontrolled system components and models of the control requirements. Although synthesis is an automatic procedure, creating these models is still a manual activity prone to modeling errors. In this paper, we propose to use several DSM-supported analysis techniques to identify potential modeling errors. Analyzing the dependencies between uncontrolled system component models and requirement models with both a domain mapping matrix and a dependency structure matrix reveals potential modeling errors. We present several examples of models from literature to show the potential effectiveness of the DSM-supported analysis of the uncontrolled system and the associated control requirements.

Original language	English
Title of host publication	Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019
Editors	Harold Stowe, Tyson R. Browning, Steven D. Eppinger, Jintin Tran, Paulo Montijo
Place of Publication	Glasgow
Publisher	Design Society
Pages	121-129
Number of pages	9
ISBN (Electronic)	978-1-912254-06-4
DOIs	https://doi.org/10.35199/dsm2019.7
Publication status	Published - 1 Jan 2019
Event	21st International Dependency and Structure Modeling Conference, DSM 2019 - Monterey, United States Duration: 23 Sept 2019 → 25 Sept 2019

Conference

Conference	21st International Dependency and Structure Modeling Conference, DSM 2019
Country/Territory	United States
City	Monterey
Period	23/09/19 → 25/09/19

Funding

The authors thank Ferdie Reijnen for providing the different versions of the models including the modeling errors created before the published version. The authors thank Rijkswaterstaat, part of the Dutch Ministry of Infrastructure and Water Management, for providing funding for this research. In particular, the authors thank Maria Angenent, Bert van der Vegt, and Han Vogel for their feedback on the results.

Keywords

DSM
Formal methods
Mbse
Supervisory control theory

Access to Document

10.35199/dsm2019.7

Cite this

Goorden, M., van de Mortel-Fronczak, J., Etman, P., & Rooda, J. (2019). DSM-based analysis for the recognition of modeling errors in supervisory controller design. In H. Stowe, T. R. Browning, S. D. Eppinger, J. Tran, & P. Montijo (Eds.), Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019 (pp. 121-129). Design Society. https://doi.org/10.35199/dsm2019.7

Goorden, Martijn ; van de Mortel-Fronczak, Joanna ; Etman, Pascal et al. / DSM-based analysis for the recognition of modeling errors in supervisory controller design. Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019. editor / Harold Stowe ; Tyson R. Browning ; Steven D. Eppinger ; Jintin Tran ; Paulo Montijo. Glasgow : Design Society, 2019. pp. 121-129

@inproceedings{c79efe6c01704fbea1debeb621c1bd02,

title = "DSM-based analysis for the recognition of modeling errors in supervisory controller design",

abstract = "The design of supervisory controllers for cyber-physical systems is steadily becoming harder as increasingly more functionality needs to be automated, the systems become larger, and safe operation becomes more important. Model-based systems engineering incorporating formal methods such as supervisory control synthesis can be used to synthesize these supervisory controllers based on models of the uncontrolled system components and models of the control requirements. Although synthesis is an automatic procedure, creating these models is still a manual activity prone to modeling errors. In this paper, we propose to use several DSM-supported analysis techniques to identify potential modeling errors. Analyzing the dependencies between uncontrolled system component models and requirement models with both a domain mapping matrix and a dependency structure matrix reveals potential modeling errors. We present several examples of models from literature to show the potential effectiveness of the DSM-supported analysis of the uncontrolled system and the associated control requirements.",

keywords = "DSM, Formal methods, Mbse, Supervisory control theory",

author = "Martijn Goorden and \{van de Mortel-Fronczak\}, Joanna and Pascal Etman and Jacobus Rooda",

year = "2019",

month = jan,

day = "1",

doi = "10.35199/dsm2019.7",

language = "English",

pages = "121--129",

editor = "Harold Stowe and Browning, \{Tyson R.\} and Eppinger, \{Steven D.\} and Jintin Tran and Paulo Montijo",

booktitle = "Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019",

publisher = "Design Society",

note = "21st International Dependency and Structure Modeling Conference, DSM 2019 ; Conference date: 23-09-2019 Through 25-09-2019",

}

Goorden, M , van de Mortel-Fronczak, J , Etman, P & Rooda, J 2019, DSM-based analysis for the recognition of modeling errors in supervisory controller design. in H Stowe, TR Browning, SD Eppinger, J Tran & P Montijo (eds), Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019. Design Society, Glasgow, pp. 121-129, 21st International Dependency and Structure Modeling Conference, DSM 2019, Monterey, United States, 23/09/19. https://doi.org/10.35199/dsm2019.7

DSM-based analysis for the recognition of modeling errors in supervisory controller design. / Goorden, Martijn ; van de Mortel-Fronczak, Joanna ; Etman, Pascal et al.
Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019. ed. / Harold Stowe; Tyson R. Browning; Steven D. Eppinger; Jintin Tran; Paulo Montijo. Glasgow: Design Society, 2019. p. 121-129.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - DSM-based analysis for the recognition of modeling errors in supervisory controller design

AU - Goorden, Martijn

AU - van de Mortel-Fronczak, Joanna

AU - Etman, Pascal

AU - Rooda, Jacobus

PY - 2019/1/1

Y1 - 2019/1/1

N2 - The design of supervisory controllers for cyber-physical systems is steadily becoming harder as increasingly more functionality needs to be automated, the systems become larger, and safe operation becomes more important. Model-based systems engineering incorporating formal methods such as supervisory control synthesis can be used to synthesize these supervisory controllers based on models of the uncontrolled system components and models of the control requirements. Although synthesis is an automatic procedure, creating these models is still a manual activity prone to modeling errors. In this paper, we propose to use several DSM-supported analysis techniques to identify potential modeling errors. Analyzing the dependencies between uncontrolled system component models and requirement models with both a domain mapping matrix and a dependency structure matrix reveals potential modeling errors. We present several examples of models from literature to show the potential effectiveness of the DSM-supported analysis of the uncontrolled system and the associated control requirements.

AB - The design of supervisory controllers for cyber-physical systems is steadily becoming harder as increasingly more functionality needs to be automated, the systems become larger, and safe operation becomes more important. Model-based systems engineering incorporating formal methods such as supervisory control synthesis can be used to synthesize these supervisory controllers based on models of the uncontrolled system components and models of the control requirements. Although synthesis is an automatic procedure, creating these models is still a manual activity prone to modeling errors. In this paper, we propose to use several DSM-supported analysis techniques to identify potential modeling errors. Analyzing the dependencies between uncontrolled system component models and requirement models with both a domain mapping matrix and a dependency structure matrix reveals potential modeling errors. We present several examples of models from literature to show the potential effectiveness of the DSM-supported analysis of the uncontrolled system and the associated control requirements.

KW - DSM

KW - Formal methods

KW - Mbse

KW - Supervisory control theory

UR - https://www.scopus.com/pages/publications/85075453569

U2 - 10.35199/dsm2019.7

DO - 10.35199/dsm2019.7

M3 - Conference contribution

SP - 121

EP - 129

BT - Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019

A2 - Stowe, Harold

A2 - Browning, Tyson R.

A2 - Eppinger, Steven D.

A2 - Tran, Jintin

A2 - Montijo, Paulo

PB - Design Society

CY - Glasgow

T2 - 21st International Dependency and Structure Modeling Conference, DSM 2019

Y2 - 23 September 2019 through 25 September 2019

ER -

Goorden M , van de Mortel-Fronczak J , Etman P, Rooda J. DSM-based analysis for the recognition of modeling errors in supervisory controller design. In Stowe H, Browning TR, Eppinger SD, Tran J, Montijo P, editors, Proceedings of the 21st International Dependency and Structure Modeling Conference, DSM 2019. Glasgow: Design Society. 2019. p. 121-129 doi: 10.35199/dsm2019.7

DSM-based analysis for the recognition of modeling errors in supervisory controller design

Abstract

Conference

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this