Grey Signal Predictor and Fuzzy Controls for Active Vehicle Suspension Systems via Lyapunov Theory

Autor:	John C. Y. Chen, Yu Ching Huang, Samiur Rahman, Chih Ching Hung, Tim Chen, Towfiqul Islam Mozumder
Rok vydání:	2021
Předmět:	Lyapunov function Artificial neural network Computer Networks and Communications Computer science Stability (learning theory) Fuzzy logic Computer Science Applications symbols.namesake Computational Theory and Mathematics Control theory Backstepping Convergence (routing) symbols Bat algorithm
Zdroj:	INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL. 16
ISSN:	1841-9844 1841-9836
DOI:	10.15837/ijccc.2021.3.3991
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9a8d3609b9fddf4092bb832ef29d1030 https://doi.org/10.15837/ijccc.2021.3.3991 Zobrazit plný text záznamu