VHDL-AMS based genetic optimisation of mixed-physical-domain systems in automotive applications
VHDL-AMS based genetic optimisation of mixed-physical-domain systems in automotive applications
This paper presents a VHDL-AMS based genetic optimization methodology suitable for performance improvement of hardware systems in automotive applications. Models of such systems are mixedsignal (analog and digital) in which the analog parts cover mixed physical domains. A case study applying this novel method to the fuzzy logic controller (FLC) optimization in an automotive active suspension system (AASS) has been investigated. A new type of fuzzy logic membership functions with variable geometrical shapes has been proposed and optimized. In this optimization technique, VHDL-AMS is used not only for the modeling and simulation of the FLC and its underlying AASS but also for the implementation of a parallel genetic algorithm (GA). This has resulted in an integrated performance optimization system wholly implemented in the hardware description language (HDL). Results show that the proposed FLC has superior performance to that of existing FLCs that use fixed-shape membership functions.
661-670
Wang, Leran
91d2f4ca-ed47-4e47-adff-70fef3874564
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
2009
Wang, Leran
91d2f4ca-ed47-4e47-adff-70fef3874564
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
Wang, Leran and Kazmierski, Tom
(2009)
VHDL-AMS based genetic optimisation of mixed-physical-domain systems in automotive applications.
Simulation: Transactions of the Society for Modeling and Simulation International, 85 (10), .
Abstract
This paper presents a VHDL-AMS based genetic optimization methodology suitable for performance improvement of hardware systems in automotive applications. Models of such systems are mixedsignal (analog and digital) in which the analog parts cover mixed physical domains. A case study applying this novel method to the fuzzy logic controller (FLC) optimization in an automotive active suspension system (AASS) has been investigated. A new type of fuzzy logic membership functions with variable geometrical shapes has been proposed and optimized. In this optimization technique, VHDL-AMS is used not only for the modeling and simulation of the FLC and its underlying AASS but also for the implementation of a parallel genetic algorithm (GA). This has resulted in an integrated performance optimization system wholly implemented in the hardware description language (HDL). Results show that the proposed FLC has superior performance to that of existing FLCs that use fixed-shape membership functions.
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Published date: 2009
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EEE
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Local EPrints ID: 270914
URI: http://eprints.soton.ac.uk/id/eprint/270914
PURE UUID: a09c1561-28f1-4945-a488-9aaf774e4534
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Date deposited: 23 Apr 2010 10:09
Last modified: 23 May 2018 16:37
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Author:
Tom Kazmierski
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