FPGA-in-the-Loop for Control Emulation of Distributed MEMS Simulation Using VHDL-AMS

Chapuis, Y.A.; Zhou, Longwen; Casner, Didier; Hong, Ai; Hervé, Y.

doi:10.1109/dmems.2010.21

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…Finally other FPGAs applications in this list includes Hardware-In-the-Loop (HIL) [34,1115,[1276][1277][1278][1279][1280][1281][1282], GPS (Global Positioning System) [1283][1284][1285][1286][1287][1288][1289][1290][1291][1292][1293][1294][1295][1296][1297][1298], Positron Emission Tomography (PET) , bioinformatics [1325][1326][1327][1328][1329][1330][1331][1332][1333][1334][1335][1336][1337][1338][1339][1340][1341][1342], fuzzy logic [1343][1344][1345][1346][1347]…”

Section: Other Applicationsmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.

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Section: Other Applicationsmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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“…d) Modeling: Two complementary models of the Smart Surface have been proposed. The VHDL-AMS model [34] can simulate the behavior of the surface at a physical level while the SysML model [35] gives a more higher-level description of the architecture. The SysML model is derived from the VHDL-AMS one and the objective is to link the SysML description of the hardware to the UML description of the software.…”

Section: A Presentationmentioning

confidence: 99%

Towards Usage of Wireless MEMS Networks in Industrial Context

Minet

Bourgeois

2012

2012 Second Workshop on Design, Control and Software Implementation for Distributed MEMS

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Industrial applications have specific needs which require dedicated solutions. On the one hand, MEMS can be used as affordable and tailored solution while on the other hand, wireless sensor networks (WSNs) enhance the mobility and give more freedom in the design of the overall architecture. Integrating these two technologies would allow more optimal solutions in terms of adaptability, ease of deployment and reconfigurability. The objective of this article is to define the new challenges that will have to be solved in the specific context of wireless MEMS networks applied to industrial applications. To illustrate the current state of development of this domain, two projects are presented: the Smart Blocks project and the OCARI project.

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“…Modeling and simulation have proven to be efficient to solve design issues [10] but new solutions have to be found to increase MEMS robustness.…”

Section: Designing Robust Memsmentioning

confidence: 99%

“…The VHDL-AMS model [10] that have been developed inside the Smart Surface project can simulate the behavior of the surface while the SysML model [16] gives a more higher-level description of the architecture. The SysML model is derived from the VHDL-AMS one and the objective is to link the SysML description of the hardware to the UML description of the software.…”

Section: Modelingmentioning

confidence: 99%

Distributed Intelligent MEMS: Progresses and Perspectives

Bourgeois

Goldstein

2015

IEEE Systems Journal

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MEMS research has until recently focused mainly on the engineering process, resulting in interesting products and a growing market. To fully realize the promise of MEMS, the next step is to add embedded intelligence. With embedded intelligence, the scalability of manufacturing will enable distributed MEMS systems consisting of thousands or millions of units which can work together to achieve a common goal. However, before such systems can become a reallity, we must come to grips with the challenge of scalability which will require paradigm-shifts both in hardware and software. Furthermore, the need for coordinated actuation, programming, communication and mobility management raises new challenges in both control and programming. The objective of this article is to report the progresses made by taking the example of two research projects and by giving the remaining challenges and the perspectives of distributed intelligent MEMS.

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FPGA-in-the-Loop for Control Emulation of Distributed MEMS Simulation Using VHDL-AMS

Cited by 6 publications

References 7 publications

Field Programmable Gate Array Applications—A Scientometric Review

Field Programmable Gate Array Applications—A Scientometric Review

Towards Usage of Wireless MEMS Networks in Industrial Context

Distributed Intelligent MEMS: Progresses and Perspectives

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