Identification of stochastic time lag systems in the presence of colored noise

Abstract

This paper is concerned with identification of stochastic time lag systems corrupted by colored noise. Correlation analysis is used for time delay estimation. Some important extensions are made via time series analysis so that the time delay can be estimated accurately even when the input to the identified plant is a common stationary signal and is correlated with the process noise. By applying a new modified least-squares estimation method to eliminating the bias in the system parameters estimates arising from colored noise, an unbiased identification algorithm for jointly estimating the time delay and system parameters can be obtained based on correlation analysis. The proposed identification schemes may be used both in batches and recursively. Numerical examples are given as well.