A novel fuzzy-sliding automatic speed control of intelligent vehicles with adaptive boundary layer

Since the vehicle longitudinal dynamic system inherently has non-linear and time-varying behaviour, it is a challenging work to design an effective automatic speed control strategy to handle the unknown nonlinearities and uncertain parameters. In this paper, a novel adaptive fuzzy sliding automatic speed controller with variable boundary layer for intelligent vehicles is proposed; the control gains and the boundary layer thicknesses of the sliding mode speed controller are adaptively tuned by fuzzy logic simultaneously. Additionally, the stability of the proposed closed-loop automatic speed control system is guaranteed by the Lyapunov theory, and the switching criterion between the throttle and brake actuators is introduced. Finally, the performance of the proposed control scheme is evaluated by simulation and experimental tests, and the results illustrate that the proposed scheme can achieve good tracking performance.

• Record URL:
  https://doi.org/10.1504/IJVD.2017.083420
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14775360
• Supplemental Notes:
  • Copyright © 2017 Inderscience Enterprises Ltd.
• Authors:
  • Guo, Jinghua
  • Luo, Yugong
  • Li, Keqiang
  • Wang, Rongben
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 300-318
• Serial:
  • International Journal of Vehicle Design
  • Volume: 73
  • Issue Number: 4
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1477-5360
  • Serial URL: http://www.inderscience.com/jhome.php?jcode=IJVD

Subject/Index Terms

• TRT Terms: Adaptive control; Automatic speed control; Fuzzy controllers; Intelligent vehicles; Longitudinal control; Simulation; Sliding mode control; Speed; Vehicle dynamics
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01635540
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 7 2017 4:13PM