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Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine
Joint Authors
Wong, Pak-kin
Vong, Chi Man
Wong, Hang-cheong
Source
Journal of Control Science and Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-23
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda) among all the engine variables.
An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term.
This paper utilizes an emerging technique, relevance vector machine (RVM), to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model.
The paper also presents a new model predictive control (MPC) algorithm for air-ratio regulation based on RVM.
This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN) and decremental least-squares support vector machine (DLSSVM).
Moreover, the control algorithm has been implemented on a real car to test.
Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC) is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI) controller in production cars.
Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.
American Psychological Association (APA)
Wong, Hang-cheong& Wong, Pak-kin& Vong, Chi Man. 2012. Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine. Journal of Control Science and Engineering،Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-494249
Modern Language Association (MLA)
Wong, Hang-cheong…[et al.]. Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine. Journal of Control Science and Engineering No. 2012 (2012), pp.1-15.
https://search.emarefa.net/detail/BIM-494249
American Medical Association (AMA)
Wong, Hang-cheong& Wong, Pak-kin& Vong, Chi Man. Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine. Journal of Control Science and Engineering. 2012. Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-494249
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-494249