Authors:
Nelio Pastor
;
Juan J. Flores
;
Claudio R. Fuerte
and
Felix Calderón
Affiliation:
Universidad Michoacana de San Nicolás de Hidalgo, División de Estudios de Postgrado, Facultad de Ingeniería Eléctrica, Mexico
Keyword(s):
Time-varying systems, LTI systems, Genetic Algorithms, Frozen-time approximation, Gradient optimization, System Identification.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Identification
;
Time Series and System Modeling
Abstract:
A method for structural and parameter identification of a slowly time-varying systems is proposed. The frozen-time method is used in this analysis. By means of this method we obtain consecutive LTI models, which are identified in consecutive discrete instants using the Qualitative System Identification (QSI) Algorithm. The proposed algorithm models the behavior of the ODE’s coefficients means of polynomial functions. The algorithm models the variations of those coefficients though polynomials. An optimal model is obtained using Genetic Algorithms. The algorithm starts with a polynomial of second degree and tries to fit these polynomials, to the variations of the coefficients. If the degree of the polynomials is not enough it increases and repeats the process until achieving a good fit. The system was tested with the identification of a controlled experiment in a power systems laboratory.