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VHDL-AMS based genetic optimisation of fuzzy logic controllers

VHDL-AMS based genetic optimisation of fuzzy logic controllers
VHDL-AMS based genetic optimisation of fuzzy logic controllers
Purpose – This paper presents a VHDL-AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance. Design/methodology/approach – The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL-AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench. Findings – Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular-shape, triangular or trapezoidal membership functions. Research limitations – The test of the FLC has only been done in the simulation stage, no physical prototype has been made. Originality/value – This paper proposes a novel way of improving the FLC’s performance and a new application area for VHDL-AMS.
Fuzzy logic, Genetics, Algorithmic languages
0332-1649
452-465
Wang, Leran
91d2f4ca-ed47-4e47-adff-70fef3874564
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
Wang, Leran
91d2f4ca-ed47-4e47-adff-70fef3874564
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a

Wang, Leran and Kazmierski, Tom (2007) VHDL-AMS based genetic optimisation of fuzzy logic controllers. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 26 (2), 452-465.

Record type: Article

Abstract

Purpose – This paper presents a VHDL-AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance. Design/methodology/approach – The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL-AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench. Findings – Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular-shape, triangular or trapezoidal membership functions. Research limitations – The test of the FLC has only been done in the simulation stage, no physical prototype has been made. Originality/value – This paper proposes a novel way of improving the FLC’s performance and a new application area for VHDL-AMS.

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More information

Published date: January 2007
Keywords: Fuzzy logic, Genetics, Algorithmic languages
Organisations: EEE

Identifiers

Local EPrints ID: 263724
URI: https://eprints.soton.ac.uk/id/eprint/263724
ISSN: 0332-1649
PURE UUID: 082ef530-7471-4e3c-a7f8-7e1e72562ade

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Date deposited: 22 Mar 2007
Last modified: 19 Jul 2019 22:28

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Contributors

Author: Leran Wang
Author: Tom Kazmierski

University divisions

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