VHDL-AMS based genetic optimisation of fuzzy logic controllers
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.
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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.
|Keywords:||Fuzzy logic, Genetics, Algorithmic languages|
|Divisions:||Faculty of Physical and Applied Science > Electronics and Computer Science > EEE
|Date Deposited:||22 Mar 2007|
|Last Modified:||26 Apr 2013 03:54|
|Contributors:||Wang, Leran (Author)
Kazmierski, Tom (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||0|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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