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Hybrid Model Predictive Controller for Engine Air-ratio Control
Wong, P. K.; Wong, H.C.; Vong, C. M.; Iong, T.M.
2015-03-01
Source PublicationProceedings of 13th International Conference on Control, Automation, Robotics and Vision
Pages181-186
Publication PlaceU.S.A.
PublisherIEEE
AbstractAir-ratio is an important engine parameter which relates closely to engine emissions, power, and brake-specific fuel consumption. Model predictive controller (MPC) is a well-known technique for air-ratio control. This paper utilizes two advanced techniques, discrete wavelet transformation (DWT) and relevance vector machine (RVM), to develop wavelet relevance vector machine model predictive controller (W-MPC) for air-ratio regulation. To compensate for the modelling error of W-MPC and system disturbances, the W-MPC is proposed to connect in parallel with a proportional-integral (PI) controller so as to form a new hybrid model predictive controller (H-MPC). The proposed H-MPC is implemented on a real engine to evaluate its effectiveness. Its control performance is also compared with the W-MPC without PI controller and the latest MPC for engine air-ratio control in the literature. Experimental results show the superiority of the proposed H-MPC over the other two controllers, which can more effectively regulate the air-ratio to target values under external disturbance. Therefore, the proposed H-MPC is a promising scheme for engine air-ratio control.
KeywordEngine air-ratio wavelet relevance vector machine model predictive control discrete wavelet transform
Language英語English
The Source to ArticlePB_Publication
PUB ID15747
Document TypeConference paper
CollectionFaculty of Science and Technology
Corresponding AuthorWong, P. K.
Recommended Citation
GB/T 7714
Wong, P. K.,Wong, H.C.,Vong, C. M.,et al. Hybrid Model Predictive Controller for Engine Air-ratio Control[C], U.S.A.:IEEE, 2015, 181-186.
APA Wong, P. K.., Wong, H.C.., Vong, C. M.., & Iong, T.M. (2015). Hybrid Model Predictive Controller for Engine Air-ratio Control. Proceedings of 13th International Conference on Control, Automation, Robotics and Vision, 181-186.
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