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FPGA Design Methodology for Industrial Control Systems—A Review

Open access
Monmasson, E., Cirstea, M.N.·2007·IEEE Transactions on Industrial Electronics

Abstract

This paper reviews the state of the art of field- programmable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic.

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Metadata

Authors
Monmasson, E., & Cirstea, M. N.
Venue
IEEE Transactions on Industrial Electronics
Published
2007-08
Volume
54
Issue
4
Pages
1824-1842
ISSN
0278-0046 (ISSN-L)
OpenAlex
W2129788823
Cited by
908
References
16
FWCI
129.72
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: FPGA Design Methodology for Industrial Control Systems—A Review. https://app.cochat.ai/papers/10.1109/tie.2007.898281
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Monmasson, E., & Cirstea, M. N. (2007). FPGA Design Methodology for Industrial Control Systems—A Review. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2007.898281

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.