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

  • Tim Chen
  • Chih Ching Hung
  • Yu Ching Huang
  • John C.Y. Chen
  • Samiur Rahman
  • Towfiqul Islam Mozumder


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.

Author Biographies

Tim Chen
Faculty of Information TechnologyTon Duc Thang University, Ho Chi Minh City, Vietnam 
Chih Ching Hung
Department of Mechanical Engineering, National Taiwan University, Taipei, TaiwanFaculty of Electronic Engineering, Taipei Municipal Muzha Vocational High School, Taipei, Taiwan
Yu Ching Huang
Department of Earth Science, National Taiwan Normal University, Taipei, TaiwanCenter of Natural Science, Kaohsiung Municipal Fushan Junior High School, Kaohsiung, Taiwan
John C.Y. Chen
Department of Artificial IntelligenceUniversity of Maryland, USA
Samiur Rahman
School of Engineering and Physical SciencesNorth South University, Dhaka, Bangladesh
Towfiqul Islam Mozumder
School of Engineering and Physical SciencesNorth South University, Dhaka, Bangladesh


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How to Cite
CHEN, Tim et al. Grey Signal Predictor and Fuzzy Controls for Active Vehicle Suspension Systems via Lyapunov Theory. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 16, n. 3, june 2021. ISSN 1841-9844. Available at: <>. Date accessed: 22 may 2022.