Abstract
In recent developments of nano technology, there are demands of controlling mechanical systems in nano meter orders. For this purpose, we need a plant model which describes the behaviors in the nano orders. In system identification of continuous-time plants, we commonly use digital data converted from analog signals. Since digital variables are of finite wordlengths, the digital data contain quantization errors. Such errors may deteriorate identification accuracy significantly, especially in the case of mechanical systems where both large movement and precise positioning are required. To overcome this problem, the present paper proposes estimation of the quantization errors and thus true sampled analog signals to improve identification accuracy. Estimates of quantization errors and system parameters are computed simultaneously. By simulation, it is illustrated that accurate results can be obtained by the proposed method.
