• DocumentCode
    1625429
  • Title

    Adaptive neuro-fuzzy controller for vehicle suspension system

  • Author

    Kalaivani, R. ; Lakshmi, P.

  • Author_Institution
    Electr. Eng. Dept., Anna Univ., Guindy, India
  • fYear
    2013
  • Firstpage
    236
  • Lastpage
    240
  • Abstract
    This paper presents, a simple and robust Adaptive Neuro-Fuzzy Inference System (ANFIS) for vibration control of a Vehicle Active Suspension System (VASS) and compares with conventional Proportional, Integral and Derivative (PID) controller and an Artificial Neural Network (ANN) controller which is trained with conventional control data. The main objective is to enhance the travelling comfort to the passengers with the use of controllers for VASS when subjected to road disturbance. The simulation is carried out using MATLAB/SIMULINK software. Simulation results show that the ANFIS works well for the suppression of the vibration of vehicle body acceleration when subjected to random road excitation compared to passive system, PID and ANN controller based active systems.
  • Keywords
    control engineering computing; fuzzy control; neurocontrollers; road traffic control; suspensions (mechanical components); three-term control; traffic engineering computing; vibration control; ANFIS; ANN controller based active systems; Matlab-Simulink software; PID controller; VASS; adaptive neuro-fuzzy controller; adaptive neuro-fuzzy inference system; artificial neural network; passive system; proportional-integral-derivative controller; road disturbance; travelling comfort; vehicle active suspension system; vehicle body acceleration; vibration control; Adaptation models; Artificial neural networks; Indexes; MATLAB; Mathematical model; Suspensions; Training; ANFIS; ANN; PID; Simulation; Suspensions; Vibration control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computing (ICoAC), 2013 Fifth International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4799-3447-8
  • Type

    conf

  • DOI
    10.1109/ICoAC.2013.6921956
  • Filename
    6921956