Optimization of Higher-Order Sliding Mode Control Parameter using Particle Swarm Optimization for Lateral Dynamics of Autonomous Vehicles

EasyChair Preprint 2844

Abstract

In this paper, we develop a strategy for lateral control of an autonomous vehicle using a higher-order sliding mode control by the super-twisting algorithm. We minimize the lateral displacement of the autonomous vehicle to a reference trajectory. And more particularly we used a Particle Swarm Optimization (PSO) algorithm to optimize the Control parameters of the higher-order Sliding Mode. In the simulation, We have followed two scenarios, the first is to optimize the sliding surface parameter and the second scenario based on the optimization of the control parameters. In this system the command input is the steering angle and the output is the lateral error. The simulation show that the control results by higher-order sliding mode control with parameters optimization PSO are better than those of the control by sliding mode control  random.

Keyphrases: PSO (Particle Swarm Optimization ), SMC (Sliding Mode Control ), autonomous vehicles, lateral dynamics

@booklet{EasyChair:2844,
  author    = {Rachid Alika and El Mehdi Mellouli and El Houssaine Tissir},
  title     = {Optimization of Higher-Order Sliding Mode Control Parameter using Particle Swarm Optimization for Lateral Dynamics of Autonomous Vehicles},
  howpublished = {EasyChair Preprint 2844},
  year      = {EasyChair, 2020}}