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Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors
This paper describes a novel design methodology using non-linear models for complex closed loop electro-mechanical sigma-delta modulators (EMΣΔM) that is based on genetic algorithms and statistical variation analysis. The proposed methodology is capable of quickly and efficiently designing high perf...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231270/ https://www.ncbi.nlm.nih.gov/pubmed/22163691 http://dx.doi.org/10.3390/s111009217 |
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author | Wilcock, Reuben Kraft, Michael |
author_facet | Wilcock, Reuben Kraft, Michael |
author_sort | Wilcock, Reuben |
collection | PubMed |
description | This paper describes a novel design methodology using non-linear models for complex closed loop electro-mechanical sigma-delta modulators (EMΣΔM) that is based on genetic algorithms and statistical variation analysis. The proposed methodology is capable of quickly and efficiently designing high performance, high order, closed loop, near-optimal systems that are robust to sensor fabrication tolerances and electronic component variation. The use of full non-linear system models allows significant higher order non-ideal effects to be taken into account, improving accuracy and confidence in the results. To demonstrate the effectiveness of the approach, two design examples are presented including a 5th order low-pass EMΣΔM for a MEMS accelerometer, and a 6th order band-pass EMΣΔM for the sense mode of a MEMS gyroscope. Each example was designed using the system in less than one day, with very little manual intervention. The strength of the approach is verified by SNR performances of 109.2 dB and 92.4 dB for the low-pass and band-pass system respectively, coupled with excellent immunities to fabrication tolerances and parameter mismatch. |
format | Online Article Text |
id | pubmed-3231270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-32312702011-12-07 Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors Wilcock, Reuben Kraft, Michael Sensors (Basel) Article This paper describes a novel design methodology using non-linear models for complex closed loop electro-mechanical sigma-delta modulators (EMΣΔM) that is based on genetic algorithms and statistical variation analysis. The proposed methodology is capable of quickly and efficiently designing high performance, high order, closed loop, near-optimal systems that are robust to sensor fabrication tolerances and electronic component variation. The use of full non-linear system models allows significant higher order non-ideal effects to be taken into account, improving accuracy and confidence in the results. To demonstrate the effectiveness of the approach, two design examples are presented including a 5th order low-pass EMΣΔM for a MEMS accelerometer, and a 6th order band-pass EMΣΔM for the sense mode of a MEMS gyroscope. Each example was designed using the system in less than one day, with very little manual intervention. The strength of the approach is verified by SNR performances of 109.2 dB and 92.4 dB for the low-pass and band-pass system respectively, coupled with excellent immunities to fabrication tolerances and parameter mismatch. Molecular Diversity Preservation International (MDPI) 2011-09-27 /pmc/articles/PMC3231270/ /pubmed/22163691 http://dx.doi.org/10.3390/s111009217 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Wilcock, Reuben Kraft, Michael Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors |
title | Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors |
title_full | Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors |
title_fullStr | Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors |
title_full_unstemmed | Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors |
title_short | Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors |
title_sort | genetic algorithm for the design of electro-mechanical sigma delta modulator mems sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231270/ https://www.ncbi.nlm.nih.gov/pubmed/22163691 http://dx.doi.org/10.3390/s111009217 |
work_keys_str_mv | AT wilcockreuben geneticalgorithmforthedesignofelectromechanicalsigmadeltamodulatormemssensors AT kraftmichael geneticalgorithmforthedesignofelectromechanicalsigmadeltamodulatormemssensors |