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

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...

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Bibliographic Details
Published in:International journal of computers, communications & control communications & control, 2021-06, Vol.16 (3)
Main Authors: Chen, Tim, Hung, Chih Ching, Huang, Yu Ching, Chen, John C.Y., Rahman, Samiur, Islam Mozumder, Towfiqul
Format: Article
Language:English
Subjects:
Active control
Adaptive algorithms
Adaptive control
Control stability
Controllers
Fuzzy control
Fuzzy logic
Neural networks
Suspension systems
Vehicle wheels
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Summary: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.
ISSN:1841-9836
1841-9844
DOI:10.15837/ijccc.2021.3.3991