Volume 9 Number 1(Jun. 2017)
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IJCEE 2017 Vol.9(1): 393-402 ISSN: 1793-8163
DOI: 10.17706/IJCEE.2017.9.1.393-402

Assessing Complexity of Component-Based Control Architectures Used in

Bugra Alkan, Daniel Vera, Malarvizhi Kaniappan Chinnathai, Robert Harrison
Abstract—Abstract: Component-based development (CBD) supports hierarchical decomposition of manufacturing control architectures through data and procedural abstraction, allowing designers to handle system development complexity better than function-oriented methods. Although the CBD approach helps managing complexity of the software design and development process, it does not reduce or eliminate complexity of control systems. In fact, large and highly coupled system architectures make entire software very difficult to understand and modify, especially during manufacturing system re-configuration and scale up/down processes. Therefore, it is essential to maintain simplicity in control system design, without disregarding the required modularity and functionality. This paper proposes an information-theoretic measure to quantify the complexity of component-based manufacturing control systems. The proposed measure is tested over the auto-generated control codes of Festo MPS system for its validity. The authors believe that the proposed approach can serve as a proactive design support, especially useful for early design stages as it allows designers to select the optimal control architectures with least complexity and provides a clear understanding of the potential stress points.

Index Terms—Key words: Complexity, component-based development, distributed control, software metrics, information theory.

Automation Systems Group, WMG, University of Warwick, CV4 7AL, Coventry, West Midlands, UK.

Cite:Bugra Alkan, Daniel Vera, Malarvizhi Kaniappan Chinnathai, Robert Harrison, "Assessing Complexity of Component-Based Control Architectures Used in Modular Automation Systems," International Journal of Computer and Electrical Engineering vol. 9, no. 1, pp. 393-402, 2017.

General Information

ISSN: 1793-8163
Frequency: Semiyearly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, Engineering & Technology Digital Library, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

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