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Adaptive Control of Vehicle Yaw Rate with Active Steering System and Extreme Learning Machine
Pak Kin Wong1; Wei Huang1; Ka In Wong2; Chi Man Vong3
2017
Conference NameInternational Conference on Extreme Learning Machine
Source PublicationProceedings of ELM
Conference Date4-7 October
Conference PlaceYatai, China
Abstract

The active steering system can enhance the vehicle yaw stability, which is essential to road safety. However, control of vehicle yaw rate is very challenging due to the presence of nonlinearity and uncertainties in the vehicle dynamics. To address the problems, an extreme-learning-machine (ELM)-based adaptive control algorithm is proposed, and a vehicle dynamic model is also developed to identify the necessary exogenous variables for control system inputs. To validate the performance of the proposed controller, simulation is conducted with an industry software. Simulation result indicates that the proposed controller achieves superior performance in tracking nominal vehicle yaw rate. A comparison is also carried out with fuzzy logic control. The pilot result shows that the proposed controller outperforms the fuzzy logic control.

KeywordAdaptive Elm Control Active Steering Vehicle Yaw Rate Control
DOIhttps://doi.org/10.1007/978-3-030-01520-6_1
Language英语
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Document TypeConference paper
CollectionFaculty of Science and Technology
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Electromechanical Engineering,University of Macau,Macau,China
2.Institute for the Development and Quality,Macau,China
3.Department of Computer and Information Science, University of Macau, Macau, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Pak Kin Wong,Wei Huang,Ka In Wong,et al. Adaptive Control of Vehicle Yaw Rate with Active Steering System and Extreme Learning Machine[C],2017.
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