Genetic-based automated synthesis and optimization of MEMS accelerometers with Sigma-Delta control
Genetic-based automated synthesis and optimization of MEMS accelerometers with Sigma-Delta control
This contribution presents a novel methodology for automated optimal layout synthesis of MEMS systems embedded in electronic control circuitry from user defined high-level performance specifications and design constraints. The proposed approach is based on simulation-based optimization where automated configuration selection for electronic blocks and synthesis of mechanical layouts are coupled with calculations of optimal design parameters. The underlying dedicated MEMS simulator supports distributed mechanical dynamics to enable accurate performance prediction of critical mechanical components, such as acceleration sensing elements which form an essential part of the mixed-technology control loop.
Zhao, Chenxu
87d1aa10-ef41-44bc-8969-82626aa1dd92
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
2010
Zhao, Chenxu
87d1aa10-ef41-44bc-8969-82626aa1dd92
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
Zhao, Chenxu and Kazmierski, Tom
(2010)
Genetic-based automated synthesis and optimization of MEMS accelerometers with Sigma-Delta control.
ISCAS 2010.
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Conference or Workshop Item
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Abstract
This contribution presents a novel methodology for automated optimal layout synthesis of MEMS systems embedded in electronic control circuitry from user defined high-level performance specifications and design constraints. The proposed approach is based on simulation-based optimization where automated configuration selection for electronic blocks and synthesis of mechanical layouts are coupled with calculations of optimal design parameters. The underlying dedicated MEMS simulator supports distributed mechanical dynamics to enable accurate performance prediction of critical mechanical components, such as acceleration sensing elements which form an essential part of the mixed-technology control loop.
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Published date: 2010
Venue - Dates:
ISCAS 2010, 2010-01-01
Organisations:
EEE
Identifiers
Local EPrints ID: 271340
URI: http://eprints.soton.ac.uk/id/eprint/271340
PURE UUID: 095b7a9f-004f-4c55-ba69-73d0407eebd9
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Date deposited: 05 Jul 2010 10:27
Last modified: 14 Mar 2024 09:28
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Contributors
Author:
Chenxu Zhao
Author:
Tom Kazmierski
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