Lee, Shin, Howlett, R.J., Walters, Simon and Crua, Cyril (2007) Modelling and control of internal combustion engines using intelligent techniques Cybernetics and Systems, 38 (5-6). pp. 509-533. ISSN 0196-9722Full text not available from this repository.
This article will compare two different fuzzy-derived techniques for controlling small internal combustion engine and modeling fuel spray penetration in the cylinder of a diesel internal combustion engine. The first case study is implemented using conventional fuzzy-based paradigm, where human expertise and operator knowledge were used to select the parameters for the system. The second case study used an adaptive neuro-fuzzy inference system (ANFIS), where automatic adjustment of the system parameters is affected by a neural networks based on prior knowledge. The ANFIS model was shown to achieve an improved accuracy compared to a pure fuzzy model, based on conveniently selected parameters. Future work is concentrating on the establishment of an improved neuro-fuzzy paradigm for adaptive, fast and accurate control of small internal combustion engines.
|Item Type:||Journal article|
|Subjects:||G000 Computing and Mathematical Sciences > G600 Software Engineering
H000 Engineering > H300 Mechanical Engineering > H330 Automotive Engineering
G000 Computing and Mathematical Sciences > G700 Artificial Intelligence
|DOI (a stable link to the resource):||10.1080/01969720701344293|
|Faculties:||Faculty of Science and Engineering > School of Computing, Engineering and Mathematics > Engineering and Product Design Research > Automotive Engineering|
|Depositing User:||Dr Cyril Crua|
|Date Deposited:||21 Jun 2007|
|Last Modified:||25 Mar 2015 14:59|
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