Title :
Adaptive neuro-fuzzy controller for vehicle suspension system
Author :
Kalaivani, R. ; Lakshmi, P.
Author_Institution :
Electr. Eng. Dept., Anna Univ., Guindy, India
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;
Conference_Titel :
Advanced Computing (ICoAC), 2013 Fifth International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3447-8
DOI :
10.1109/ICoAC.2013.6921956