Signal Identification In Discrete-Time Based On Internal-Model-Principle

Abstract

This work presents an implementation of a signal identification algorithm which is based on the internal model principle. By using several internal models in feedback with a tuning function, this algorithm can decompose a signal into narrow-band signals and identify the frequencies, amplitudes and relative phases. A desired band-pass filter response can be achieved by selecting appropriate coefficients of the controllers and tuning functions, which can reject the noise and improve the performance. To achieve a result with fast transient characteristics, this system is then modified by adding a low-pass filter. This work is based on the previous work in continuous time. However, a discrete implementation should be much more practical. The simulation result shows a good tracking of the original signal with minimal response to measurement noise