COMPARISON OF NEURAL NETWORK NARMA-L2 MODEL REFERENCE AND PREDICTIVE CONTROLLERS FOR NONLINEAR QUARTER CAR ACTIVE SUSPENSION SYSTEM.pdf

Mustefa Jibril
2020 Figshare  
Recently, active suspension system will become important to the vehicle industries because of its advantages inimproving road managing and ride comfort. This paper offers the development of mathematical modelling anddesign of a neural network control approach. The paper will begin with a mathematical model designing primarilybased at the parameters of the active suspension system. A nonlinear three by four-way valve-piston hydraulicactuator became advanced which will make the suspension system
more » ... nder the active condition. Then, the model canbe analyzed thru MATLAB/Simulink software program. Finally, the NARMA-L2, model reference and predictivecontrollers are designed for the active suspension system. The results are acquired after designing the simulation ofthe quarter-car nonlinear active suspension system. From the simulation end result using MATLAB/Simulink, theresponse of the system might be as compared between the nonlinear active suspension system with NARMA-L2,model reference and predictive controllers. Besides that, the evaluation has been made between the proposedcontrollers thru the characteristics of the manage objectives suspension deflection, body acceleration and body travelof the active suspension system. . As a conclusion, designing a nonlinear active suspension system with a nonlinearhydraulic actuator for quarter car model has improved the car performance by using a NARMA-L2 controller. Theimprovements in performance will improve road handling and ride comfort performance of the active suspensionsystem.
doi:10.6084/m9.figshare.12235310 fatcat:xsngsusqrjddzoq2pb4jpwu53u