Authors:
Alexander E. Robles
and
Mateus Giesbrecht
Affiliation:
School of Electrical and Computer Engineering, University of Campinas, Av. Albert Einstein 400, Campinas - SP and Brazil
Keyword(s):
Evolutionary Algorithms, Coevolutionary Algorithms, System Identification, Time-variant System Identification.
Related
Ontology
Subjects/Areas/Topics:
Evolutionary Computation and Control
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
Abstract:
A significant part of the works in system identification is focused on time-invariant dynamic systems. However, most of systems in the real applications have nonlinear and time variant behavior. In this paper, we present a multivariable time-variant identification method based on a paradigm in the field of evolutionary algorithms: The coevolutionary algorithm. This new method focuses on the relationship between the fitness of an individual in relation to the fitness of the other individuals (or group of individuals), based on the principle of the selective pressure, that is part of the evolutionary process. A brief comparison between a multivariable deterministic identification method MOESP-VAR and the proposed coevolutionary method is shown. From the results it is possible to notice that the proposed method presents an accuracy higher than the obtained with the deterministic identification method.