Longitudinal Dynamic Control under Complex Driving Conditions via Fuzzy Logic Sliding-mode Control

Ruiqi Zhang, Yuzhuang Zhao, Sizhong Chen, Zhicheng Wu, Lin Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

To track desired speed of autonomous vehicle, the longitudinal motion control algorithm was proposed based on the smooth switching between throttle actuator and brake actuator using sliding-mode control strategy. By adjusting the switching gain of the sliding-mode surface with fuzzy logic, the oscillation of the sliding-mode variable structure control system was effectively reduced. The stability of the closed-loop system was proved by Lyapunov method. The control effect was simulated under various driving processes. Simulation results show that the fuzzy logic sliding-mode control algorithm has high tracking accuracy and strong robustness even in the presence of uncertainties and external disturbances.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1161-1166
Number of pages6
ISBN (Electronic)9781728116983
DOIs
Publication statusPublished - Aug 2019
Event16th IEEE International Conference on Mechatronics and Automation, ICMA 2019 - Tianjin, China
Duration: 4 Aug 20197 Aug 2019

Publication series

NameProceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019

Conference

Conference16th IEEE International Conference on Mechatronics and Automation, ICMA 2019
Country/TerritoryChina
CityTianjin
Period4/08/197/08/19

Keywords

  • Fuzzy logic
  • Longitudinal control
  • Sliding-mode control
  • Vehicle model

Fingerprint

Dive into the research topics of 'Longitudinal Dynamic Control under Complex Driving Conditions via Fuzzy Logic Sliding-mode Control'. Together they form a unique fingerprint.

Cite this