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2023 | OriginalPaper | Chapter

Suspension of Heavy Trucks with Intelligent Control Using Artificial Neural Networks Particle Swarm Optimization (ANN-PSO)

Authors : Anis Hamza, Issam Dridi, Kamel Bousnina, Noureddine Ben Yahia

Published in: Advances in Acoustics and Vibration IV

Publisher: Springer International Publishing

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Abstract

In this paper, we discuss the motivation to create a novel active suspension control method for trucks and Heavy Goods Vehicle (HGV) based on intelligent control using hybrid Artificial Neural Network Particles Swarm Optimization (ANN-PSO). There are three types of suspension systems: passive, semi-active and active. Ride comfort, suspension travel and handling are all factors in the performance required of an active suspension system. The model was created using the MATLAB toolkit, and it was efficient and validated using information gathered from experiments using a vehicle. Modeling a system can be done in different ways. One of them is to describe the system using the rules of physics and then determine the parameters of the system using experimental data or other information used using an intelligent algorithm ANN-PSO. The objective of this research is to create a reliable hybrid intelligent controller that can improve the functionality of heavy truck nonlinear active suspension system and its validations using motion and graphic output.

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Title: Suspension of Heavy Trucks with Intelligent Control Using Artificial Neural Networks Particle Swarm Optimization (ANN-PSO)
Authors: Anis Hamza
Issam Dridi
Kamel Bousnina
Noureddine Ben Yahia
Publisher: Springer International Publishing
Book: Advances in Acoustics and Vibration IV
Print ISBN: 978-3-031-34189-2

Electronic ISBN: 978-3-031-34190-8

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-3-031-34190-8_23

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