Title: Optimal adaptive Lipschitz continuous sliding mode controller with APSO algorithm for an autonomous vehicle

Authors: Ayoub Belkheir; El Mehdi Mellouli; Vidas Žuraulis

Addresses: Laboratory of Engineering, Systems and Applications (LISA), Sidi Mohamed Ben Abdellah University, Fez, Morocco ' Laboratory of Engineering, Systems and Applications (LISA), Sidi Mohamed Ben Abdellah University, Fez, Morocco ' Department of Automobile Engineering, Vilnius Gediminas Technical University, Vilnius, Lithuania

Abstract: The paper presents a method for controlling lateral movement with uncertain and unknown dynamics for an autonomous vehicle that combines the adaptive particle swarm optimisation (APSO) algorithm and the Lipschitz continuous sliding mode controller (LCSMC). Designing the desired trajectory, and modelling the vehicle using the bicycle model is the initial step. The control law is defined using the classical Lipschitz continuous sliding mode control (LCSMC) in the following step. In the next step, the system's nonlinear functions are modelled using a radial basis function neural network (RBFNN), the developed intelligent triangular observer is proposed, and the suggested approach adaptive Lipschitz continuous sliding mode control (ALCSMC) is suggested with stability analysis using the Lyapunov function and optimising the parameters gain using APSO algorithm after. Finally, the study is finished by simulating this strategy to see their performance and effectiveness in accomplishing the desired results.

Keywords: adaptive particle swarm optimisation; APSO; autonomous vehicle; Lipschitz continuous sliding mode control; LCSMC; Lyapunov function; triangular observer.

DOI: 10.1504/IJVP.2024.140013

International Journal of Vehicle Performance, 2024 Vol.10 No.3, pp.286 - 311

Received: 14 Aug 2023
Accepted: 22 Dec 2023
Published online: 15 Jul 2024 *

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