Vibration control of a translational coupled double flexible beam system using sliding mode neural network fuzzy control

Abstract

A sliding mode neural network fuzzy control (SMNNFC) method is investigated to suppress the vibration of a translational coupled double flexible beam system, equipped with an AC servomotor and several piezoelectric actuators. Adjacent beams and slider moving frame are connected at the tip by elastic springs. Based on the finite element method, the system model is established to recognize the vibration characteristics. Furthermore, two laser displacement sensors are used to decouple the first two bending modes of the double flexible beam system. In the applied SMNNFC strategy, a neural-fuzzy framework is designed to obtain robust control performance and alleviate the chattering phenomenon. Considering unknown and varying system uncertainty, a parameter updating algorithm is adopted. The stability of SMNNFC is analyzed. The experimental setup is constructed and experiments are conducted, including set-point vibration control and simultaneous translation and vibration control under trapezoidal and sinusoidal trajectories. The experimental results demonstrate that the SMNNFC scheme has advantages in suppressing both the large and low amplitude vibrations of the coupling double flexible beam system.