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Intelligent Vibration Control for Semiactive Suspension Systems without Prior Knowledge of Dynamical Nonlinear Damper Behaviors Based on Improved Extreme Learning Machine
Huang, Wei1; Zhao, Jing2; Yu, Guokuan2; Wong, Pak Kin2
2021-08-01
Source PublicationIEEE/ASME Transactions on Mechatronics
ISSN1083-4435
Volume26Issue:4Pages:2071-2079
Abstract

Aiming at enhancing the vehicle comfort and handling performances, this article concerns with the development of the vibration control method for the semiactive suspension systems installed with electrohydraulic dampers. To reject the external disturbances induced by the irregular road profile, sliding mode was intensively investigated for vibration control owing to its robust feature of insensitivity to the parametric uncertainty and external disturbances. However, the unknown nonlinearity of damper behaviors leads to model mismatch to cause the high-frequency switching of sliding-mode controllers. Consequently, the severe chattering phenomenon produces. Although saturated function is available to alleviate the chattering problem of sliding-mode control, there is always a tradeoff problem between tracking accuracy and chattering suppression. To solve this problem, this study provides a new intelligent robust control method for simultaneous improvements of tracking accuracy and chattering suppression. Given the computational efficiency, an improved extreme learning machine (ELM) is proposed to intelligently approximate and compensate the unmodeled dynamics with unknown nonlinearity to restrain the chattering problem, where a new adaptive learning law is designed in the premise of Lyapunov stability. To validate the effectiveness and efficiency of the proposed ELM-based robust control, a quarter-car test rig was set up for the hardware-in-the-loop test. Experimental results show that the proposed controller outperforms the sliding-mode controller with saturated function in depressing the sprung mass acceleration and tire deflection, showing its significance in both control performance enhancement and chattering elimination.

KeywordChattering Elimination Electrohydraulic Damper Extreme Learning Machine (Elm) Semiactive Suspension
DOI10.1109/TMECH.2020.3031840
URLView the original
Indexed BySCIE ; CPCI-S
Language英語English
WOS Research AreaAutomation & Control Systems ; Engineering
WOS SubjectAutomation & Control Systems ; Engineering, Manufacturing ; Engineering, Electrical & Electronic ; Engineering, Mechanical
WOS IDWOS:000685886000039
Scopus ID2-s2.0-85104097760
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Cited Times [WOS]:6   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Faculty of Science and Technology
Corresponding AuthorWong, Pak Kin
Affiliation1.School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China
2.Department of Electromechanical Engineering, University of Macau, 999078, Macao
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Huang, Wei,Zhao, Jing,Yu, Guokuan,et al. Intelligent Vibration Control for Semiactive Suspension Systems without Prior Knowledge of Dynamical Nonlinear Damper Behaviors Based on Improved Extreme Learning Machine[J]. IEEE/ASME Transactions on Mechatronics,2021,26(4):2071-2079.
APA Huang, Wei,Zhao, Jing,Yu, Guokuan,&Wong, Pak Kin.(2021).Intelligent Vibration Control for Semiactive Suspension Systems without Prior Knowledge of Dynamical Nonlinear Damper Behaviors Based on Improved Extreme Learning Machine.IEEE/ASME Transactions on Mechatronics,26(4),2071-2079.
MLA Huang, Wei,et al."Intelligent Vibration Control for Semiactive Suspension Systems without Prior Knowledge of Dynamical Nonlinear Damper Behaviors Based on Improved Extreme Learning Machine".IEEE/ASME Transactions on Mechatronics 26.4(2021):2071-2079.
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