Improvement of Vibration Isolation Performance of Isolation System Using Negative Stiffness Structure

Abstract

Improvement of the isolation effectiveness of the isolation system using negative stiffness structure (NSS) named “system with NSS” by introducing an adaptive sliding mode control algorithm is presented in this paper. The control strategy is to employ a radial basis function neural network (RBFNN) model to approximate the equivalent control effort and a self-tuning proportional-integral-derivative (PID) algorithm is used to compensate approximate error. Moreover, a fuzzy logic inference mechanism is utilized for realizing an auxiliary control law to remove completely the chattering problem on the conventional sliding mode control. Then, the Lyapunov stability theorem is utilized to figure out the adaptive laws for updating the coefficients in the RBFNN model, PID compensator, and tuning the fuzzy parameters. Finally, four experimental cases of studies are performed to evaluate the proposed control method.