Study on an active vibration isolation method based on neural network

Aimed at the nonlinearities in active vibration isolation system(AVIS), an adaptive control method based on neural network was proposed. The CMAC(cerebellar model articulation control) neural network was used as controller, whose parameters were updated based on stochastic gradient descent algorithm. To reduce the influence of secondary path on controller parameters, a BP(back propagation) network was used to identify the secondary path offline. The observable error signal was combined with model parameters of the secondary path to jointly update controller parameters. Simulation results showed the proposed method has preferable effectiveness for AVIS with nonlinearities, and its capacity of vibration isolation is much better than that of FLMS(filtered least mean square).