Application of forecasting and discrete optimal controls to a servo-damper system

Abstract

This study deals with two control theories, forecasting control based on a time series analysis and discrete optimal output feedback control, applied to suppress the vibration of a cantilever by using a servo-damper controller. Preliminary experiments are carried out to determine the proper stochastic model for the system, where the noise to the servo-damper is the input and the vibration of the cantilever at its free end is the output. The best model is determined to be Bivariate ARV($\frac{4}{3}$) in consideration of the stability and effectiveness of the controller model. With the model determined, control schemes are derived for both forecasting and discrete optimal controls. To evaluate the performances of the two control schemes, experimental and simulation studies are performed. It is then found that forecasting control is better than discrete optimal control except for the noise sensitivity. The inherent noise sensitivity of forecasting control is examined and a remedy is suggested.