Fuzzy-neural network control for a magnetorheological elastomer vibration control system with sinusoidal excitations

This paper presents the design method of a fuzzy-neural network controller (FNNC) for a MRE vibration control system with sinusoidal excitations to improve the vibration attenuation. A semi-active FC is designed to obtain the conrolled force based on the feedback signals of the relative displacement and absolute displacement of the isolation structure, then the BP neural network with good learning capability is employed to emulate the dynamic behaviours of output force of fuzzy controller (FC), excitation displacement, velocity and controlled current applied to the coil in MRE isolator. The acceleration responses of the system with FNNC are evaluated by physical experiments, the results indicate that the FNNC could maintain satisfying control effect in the presence sinusoidal excitations and is also more optimal than conventional FC, the reason is that the neural network controller can approximate the nonlinear function relationship among the controlled force, excitation displacement, velocity and controlled current, but the function relationship is only considered as the linear function in conventional FC.