Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller

UM > Faculty of Science and Technology

Status	已發表Published
	Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller
	Wong, P. K.; Wong, H. C.; Vong, C. M.; Iong, T. M.; Wong, K. I.; Gao, X. H.
	2015-05-01
Source Publication	Mathematical Problems in Engineering (SCI-E)
ISSN	1563-5147
Pages	1-10
Abstract	Effective air-ratio control is desirable to maintain the best engine performance. However, traditional air-ratio control assumes the lambda sensor located at the tail pipe works properly and relies strongly on the air-ratio feedback signal measured by the lambda sensor. When the sensor is warming up during cold start or under failure, the traditional air-ratio control no longer works. To address this issue, this paper utilizes an advanced modelling technique, kernel extreme learning machine (ELM), to build a backup air-ratio model. With the prediction from the model, a limited air-ratio control performance can be maintained even when the lambda sensor does not work. Such strategy is realized as fault tolerance control. In order to verify the effectiveness of the proposed fault tolerance air-ratio control strategy, a model predictive control scheme is constructed based on the kernel ELM backup air-ratio model and implemented on a real engine. Experimental results show that the proposed controller can regulate the air-ratio to specific target values within a satisfactory tolerance under external disturbance and the absence of air-ratio feedback signal from the lambda sensor. This implies that the proposed fault tolerance air-ratio control is a promising scheme to maintain air-ratio control performance when the lambda sensor is under failure or warming up.
Keyword	Air-ratio control Extreme Learning Machine Model Predictive Control
Language	英語English
The Source to Article	PB_Publication
PUB ID	15400
Document Type	Journal article
Collection	Faculty of Science and Technology
Corresponding Author	Wong, P. K.
Recommended Citation GB/T 7714	Wong, P. K.,Wong, H. C.,Vong, C. M.,et al. Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller[J]. Mathematical Problems in Engineering (SCI-E), 2015, 1-10.
APA	Wong, P. K.., Wong, H. C.., Vong, C. M.., Iong, T. M.., Wong, K. I.., & Gao, X. H. (2015). Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller. Mathematical Problems in Engineering (SCI-E), 1-10.
MLA	Wong, P. K.,et al."Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller".Mathematical Problems in Engineering (SCI-E) (2015):1-10.

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