Master of Engineering Science
Electrical and Computer Engineering
Dr. Lyndon J. Brown
This thesis presents a new means approach of tuning an adaptive internal model principle based signal identification algorithm whose computational costs are low enough to allow a realtime implementation. The algorithm allows an instantaneous Fourier decomposition of nonstationary signals that have a strongly predictable component. The algorithm is implemented as a feedback loop resulting in a closed loop system with a frequency response of a bandpass filter with notches at the frequencies of the Fourier decomposition. This is achieved through real time selection of the coefficients of the transfer functions in the feedback loop. Previous work showed how the dynamics of the algorithm could be chosen to be represented by a bandpass filter with notches. However this involved solving a large set of coupled linear equations. This thesis shows how the equations can be decoupled into pairs of linear equations which have explicit solutions. In other word, rules for explicitly solving for these parameters are given that only involve evaluating frequency responses at the frequencies of the instantaneous Fourier decomposition. Last but not the least, alternative approach for choosing suitable coefficients to eliminate the DC component of the signal under consideration has been proposed as well by replacing a frequency response of a bandpass filter with lowpass filter and adding a model of the constant signal to the feedback loop.
Mohsen, Edris Saleh, "RealTime Implementation Of An Internal-Model-Principle Signal Identifier" (2017). Electronic Thesis and Dissertation Repository. 5009.