Title: Direct optimal fuzzy logic adapted to sliding mode for lateral autonomous vehicle control

Authors: Najlae Jennan; El Mehdi Mellouli

Addresses: Laboratory of Engineering, Systems and Applications, Sidi Mohamed Ben Abdellah University, Fez, Morocco ' Laboratory of Engineering, Systems and Applications, Sidi Mohamed Ben Abdellah University, Fez, Morocco

Abstract: In this article, a direct Takagi-Sugeno fuzzy logic controller adapted to fast terminal sliding mode has been developed to control the lateral dynamics of an autonomous vehicle under external disturbances. The strategy aims to improve the overall performance of the autonomous vehicle under varying driving conditions by exploiting the advantages of FTSMC to ensure fast convergence and reduced transient time, thereby overcoming uncertainties and the common chattering problem in sliding mode. First, we applied the direct T-S fuzzy logic controller based on FTSMC to the autonomous vehicle. To minimise both effects of uncertainties and fuzzy inaccuracy, a new adaptive control term is introduced and optimised using particle swarm optimisation and butterfly optimisation algorithm. A comparative analysis of these techniques is presented to show their advantages in improving the controller. The Lyapunov approach is employed to guarantee the system stability. The results prove the strategy's applicability for advancing overall vehicle behaviour.

Keywords: adaptive lateral control; T-S fuzzy logic; fast terminal sliding mode control; FTSMC; autonomous vehicles; particle swarm optimisation; PSO; butterfly optimisation algorithm; BOA.

DOI: 10.1504/IJVP.2024.140036

International Journal of Vehicle Performance, 2024 Vol.10 No.3, pp.349 - 372

Received: 31 Dec 2023
Accepted: 30 Mar 2024
Published online: 15 Jul 2024 *

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