Output details
12 - Aeronautical, Mechanical, Chemical and Manufacturing Engineering
Liverpool John Moores University
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Output 0 of 0 in the submission
Article title
Adaptive RBF network for parameter estimation and stable air–fuel ratio control
Type
D - Journal article
Title of journal
Neural Networks
Article number
-
Volume number
21
Issue number
1
First page of article
102
ISSN of journal
08936080
Year of publication
2008
URL
-
Number of additional authors
1
Additional information
This paper published in the flagship journal of the area presents the research findings from a collaborative research project “Fault detection and fault tolerant control for automotive engines” with the BMW E30 in Munich (Senior Specialist, BMW E30, 2004-2007). “The research findings reported are novel and can, with further tests, be effectively used for improving engine performance” (Senior Specialist, BMW E30). The paper “described a new methodological development for stable sliding mode control with adaptive neural model compensation for internal combustion engines” as commented by one of the reviewers (Co-Editor-in-Chief, Neural Networks).
Interdisciplinary
-
Cross-referral requested
-
Research group
2 - MEMARC
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
