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One ofa car's suspension system functions is to isolate vibrations resulting from road on the driver and ensure a comfortable ride. But the design of control systems for semi-active suspension systems is difficult because of the non-linearity of the constituent elements of these systems which make the researches related to it characterized by complexity. So in order to improve the performance of semi-active suspension systems without bearing the effort of designing a model based controller, a control system is designed using self-organizing fuzzy controller based on the principle of delay-in-penalty to control a semi-active suspension system which uses a magneto rheological damper. The controller tries to enhance system performance using the desired response as it is described in the penalty table. The fuzzy logic controller is based on two inputs namely sprung mass velocity and unsprung mass velocity. Using a quarter car model with 2 degree-of-freedom the system is modeled and simulated in MATLAB &Simulink® and the results are compared to the widely used sky-hook strategy. the simulation showed the ability of the self-organizing fuzzy controller to provide good results in minimizing sprung mass acceleration in variousroad profiles compared to sky-hookstrategy.
Suspension system is considered one of the most important components of modern automobiles as it is the responsible for the vehicle’s stability, balance and safety. The presence of robust controller is very necessary in order to ensure full interac tion between suspension components and making accurate decisions at the right time. This paper proposes to design an Extended Adaptive Neuro Fuzzy Inference System (EANFIS) controller for suspension system in quarter car model. The proposed controller is used as decision maker In order to contribute in absorbing shocks caused by bumpy roads, and to prevent vibrations from reaching the cockpit. Furthermore, it provides stability and coherence required to reduce the discomfort felt by passengers, which arises from road roughness, which in turn, improve the road handling. The MATLAB Simulink is used to simulate the proposed controller with the controlled model and to display the responses of the controlled model under different types of disturbance. In addition, a comparison between EANFIS controller, Fuzzy controller and open loop model (passive suspension) was done with different types of disturbance on order to evaluate the performance of the proposed model. Controller has shown excelled performance in terms of reducing displacements, velocity and acceleration.
In this paper, a problem of ride comfort enhancement in a moving vehicle was introduced and controlled by damping force to deduce vibration caused by road profile. Sliding mode control was used to give the damping force in two degree of freedom su spension system. A mechanic model of suspension system was given, dampers and springs were used for passive damping to reduce chattering and sliding mode control for semi-active control with proposed method by using supervised fuzzy logic control for chattering decreasing was designed. A simulation with the given initial conditions was designed using Matlab/Simulink. By computing of root mean square error we got that the proposed method gave the best responses with the smallest chattering compared with traditional mechanical damping and sliding mode control. All results plotted using Matlab/Simulink.
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