2014MechanikaOpen access

Improve active suspension system by FEL controller design

S. Ms. Marofi, S. J. Seyedalian, L. Akram

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Abstract

Since, the area of vibration is one the most im-portant criteria which with it, human judges about the design and quality construction of the vehicle, the disturb-ances caused by road vibrations must be controlled in the vehicle suspension that ride comfort, steering and stability of the vehicle can be supplied. This is improved with active suspension system design. In this paper, fuzzy neural network controller by FEL is designed in order to improv-ing applicability of the active suspension system and then its results is compared to conventional PID and LQR con-troller. Also, the quarter model of linear and nonlinear active suspension system is simulated in the MATLAB software with the road disturbance and an actuator control force which obtained by its disturbance. Results of simulation illustrated that the deflection and acceleration of the sprung mass with this intelligent con-troller for linear model 38.9%, 46.3% and for nonlinear model 66.6%, 25% decreased respect to LQR controller and this category will be caused to increase more the ride comfort, steering and stability of the vehicle. DOI: http://dx.doi.org/10.5755/j01.mech.19.6.6010

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Since, the area of vibration is one the most im-portant criteria which with it, human judges about the design and quality construction of the vehicle, the disturb-ances caused by road vibrations must be controlled in the vehicle suspension that ride comfort, steering and stability of the vehicle can be supplied. This is improved with active suspension system design. In this paper, fuzzy neural network controller by FEL is designed in order to improv-ing applicability of the active suspension system and then its results is compared to conventional PID and LQR con-troller. Also, the quarter model of linear and nonlinear active suspension system is simulated in the MATLAB software with the road disturbance and an actuator control force which obtained by its disturbance. Results of simulation illustrated that the deflection and acceleration of the sprung mass with this intelligent con-troller for linear model 38.9%, 46.3% and for nonlinear model 66.6%, 25% decreased respect to LQR controller and this category will be caused to increase more the ride comfort, steering and stability of the vehicle. DOI: http://dx.doi.org/10.5755/j01.mech.19.6.6010

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Available abstract

Since, the area of vibration is one the most im-portant criteria which with it, human judges about the design and quality construction of the vehicle, the disturb-ances caused by road vibrations must be controlled in the vehicle suspension that ride comfort, steering and stability of the vehicle can be supplied. This is improved with active suspension system design. In this paper, fuzzy neural network controller by FEL is designed in order to improv-ing applicability of the active suspension system and then its results is compared to conventional PID and LQR con-troller. Also, the quarter model of linear and nonlinear active suspension system is simulated in the MATLAB software with the road disturbance and an actuator control force which obtained by its disturbance. Results of simulation illustrated that the deflection and acceleration of the sprung mass with this intelligent con-troller for linear model 38.9%, 46.3% and for nonlinear model 66.6%, 25% decreased respect to LQR controller and this category will be caused to increase more the ride comfort, steering and stability of the vehicle. DOI: http://dx.doi.org/10.5755/j01.mech.19.6.6010

Key concepts: Sprung mass, Active suspension, Control theory (sociology), Nonlinear system, Engineering, MATLAB, PID controller, Vibration

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