Abstract

In order to investigate and decide that the vehicle asymptotic vibration stability and improved comfort, the present paper deals with a fuzzy neural network (NN) evolved bat algorithm (EBA) backstepping adaptive controller based on grey signal predictors. The Lyapunov theory and backstepping method is utilized to appraise the math nonlinearity in the active vehicle suspension as well as acquire the final simulation control law in order to track the suitable signal. The Discrete Grey Model DGM (2,1) have been thus used to acquire prospect movement of the suspension system, so that the command controller can prove the convergence and the stability of the entire formula through the Lyapunov-like lemma. The controller overspreads the application range of mechanical elastic vehicle wheel (MEVW) as well as lays a favorable theoretic foundation in adapting to new wheels.

Details

Title
Grey Signal Predictor and Fuzzy Controls for Active Vehicle Suspension Systems via Lyapunov Theory
Author
Chen, Tim; Hung, Chih Ching; Huang, Yu Ching; John C.Y. Chen; Rahman, Samiur; Towfiqul Islam Mozumder
Section
Articles
Publication year
2021
Publication date
Jun 2021
Publisher
Agora University of Oradea
ISSN
18419836
e-ISSN
18419844
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2546067716
Copyright
© 2021. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.