The University of Southampton
University of Southampton Institutional Repository

Automated performance optimisation and layout synthesis of MEMS accelerometer with sigma-delta force-feedback control loop

Record type: Article

This contribution presents a novel methodology for automated optimal design of a MEMS accelerometer with Sigma-Delta force-feedback control loop from user defined high-level performance specifications and design constraints. The proposed approach is based on a simulation-based optimization technology using a genetic algorithm. The layout of the mechanical sensing element is generated simultaneously with the optimal design parameters of the Sigma-Delta control loop. As currently available implementations of AMS HDL languages are not suitable for complex mixed-technology system optimisation, the algorithm as well as aa fast dedicated sigma-delta accelerometer simulator have been implemented in C++. The underlying accelerometer model includes the sense finger dynamics described by a partial differential equation, which enables accurate performance prediction of the sensing element embedded in a in mixed-technology control loop.

Full text not available from this repository.

Citation

Kazmierski, T.J. (2008) Automated performance optimisation and layout synthesis of MEMS accelerometer with sigma-delta force-feedback control loop 2008 IEEE International Behavioral Modeling and Simulation Workshop, pp. 19-24.

More information

Published date: 2008
Additional Information: Imported from ISI Web of Science
Organisations: EEE

Identifiers

Local EPrints ID: 269752
URI: http://eprints.soton.ac.uk/id/eprint/269752
PURE UUID: f386d4ad-7506-4815-b80c-956efff96567

Catalogue record

Date deposited: 21 Apr 2010 07:46
Last modified: 18 Jul 2017 06:51

Export record

Contributors

Author: T.J. Kazmierski

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×