NDLI: Robust adaptive control for vehicle active suspension systems with uncertain dynamics

Content Provider	IEEE Xplore Digital Library
Author	Yingbo Huang Jing Na Guanbin Gao Xing Wu Yu Guo
Copyright Year	2015
Description	Author affiliation: Fac. of Mech. & Electr. Eng., Kunming Univ. of Sci. & Technol., Kunming, China (Yingbo Huang; Jing Na; Guanbin Gao; Xing Wu; Yu Guo)
Abstract	This paper proposes adaptive control for vehicle active suspensions with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise damper dynamics). An adaptive control is designed to stabilize the altitude of vehicles and to improve the ride comfort, where an augmented neural network is developed to provide the online compensation for the unknown dynamics. A novel adaptive law is proposed to estimate the NN weights and essential model parameters (e.g., mass of vehicle body, inertia for pitch motion). The parameter estimation error is derived and used as a novel leakage term superimposed on the adaptation to guarantee the error convergence. Theoretical studies are provided to address the closed-loop system performance and to compare the novel adaptive law with traditional adaptive laws. The suspension space limitations and dynamic tire loads are also analyzed. Finally, comparative simulations are included to verify the effectiveness of the proposed control.
Starting Page	8033
Ending Page	8038
File Size	409022
Page Count	6
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260917
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Roads neural networks parameter estimation adaptive control Shock absorbers Active suspension systems Adaptive control Vehicle dynamics Springs Vehicles
Content Type	Text
Resource Type	Article

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