Modelling and control of internal combustion engines using intelligent techniques
Lee, S.H., Howlett, R.J., Walters, S.D. and Crua, C. (2007) Modelling and control of internal combustion engines using intelligent techniques Cybernetics and systems, 38 (5 & 6). pp. 509-533. ISSN 0196-9722
Full text not available from this repository.
Official URL: http://www.informaworld.com/openurl?genre=article&...
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.
Repository Staff Only: item control page