Decentralized neuro-fuzzy control for half car with semi-active suspension system

In this paper, a decentralized neuro-fuzzy controller has been created in order to improve the ride comfort and increase the stability for half car suspension system, which used the magneto-rheological damper as a semi-active device. Firstly, relative gain array and relative disturbance gain methods have been used for deriving a relation between inputs, disturbances and outputs to select pairing with minimum interaction to design a decentralize controller. Secondary, decentralized neuro-fuzzy controllers for front and rear chassis are designed to predict the required damping force taking the acceleration of the sprung mass and desired acceleration obtained by using pole-placement method as inputs. To predict the control voltage required for producing the force predicted by the controller, the inverse neuro-fuzzy model of MR damper has been designed. Simulation by using MATLAB programs has been created. The results show that the ride comforts and vehicle stability have been improved in comparison with the passive system.