Banca de DEFESA: ÍCARO BEZERRA QUEIROZ DE ARAÚJO

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
DISCENTE : ÍCARO BEZERRA QUEIROZ DE ARAÚJO
DATA : 26/07/2019
HORA: 15:30
LOCAL: Sala DCA 02
TÍTULO:

Maximum correntropy criterion applied to structure selection and parameter estimation of NARX models

PALAVRAS-CHAVES:

Nonlinear system identification, NARX models, Model structure selection, Correntropy.

PÁGINAS: 120
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica
SUBÁREA: Eletrônica Industrial, Sistemas e Controles Eletrônicos
ESPECIALIDADE: Controle de Processos Eletrônicos, Retroalimentação
RESUMO:

In the last decades, due to the growing complexity of dynamic systems and the growing demand for better performance, the area of systems identification has emphasized the use of non-linear models to represent dynamic systems. In this context, Non-linear autoregressive with exogenous inputs models (NARX) are heavily used due to to their simplicity, flexibility and capacity of better representation. However, such models rely heavily on structure selection and the most traditional algorithms have limitations when the data is contaminated by non-gaussian distribution noises. Noting this, in this thesis, the objective is to present a new identification method called simulated correntropy maximization with pruning which uses concepts of learning based on information theory. In this work basic concepts about systems identification and correntropy, methods based on orthogonal least squares and simulated error reduction, and the new proposed methodology. The proposed method is applied and compared to the traditional methods in some study cases. The first experiment is composed by three SISO numeric dynamic systems in the presence of bimodal noise. The second study case is a set taken from a benchmark system called Silver Box. The third is a real dynamic system. The fourth and last one is a real dynamic MIMO coupled-tanks system. The obtained results validate the performance of the proposed method when compared to other algorithms of structure detection and parameter estimation, showing that the proposed method presents a better and more robust performance in the presence of non-gaussian distribution noise.

MEMBROS DA BANCA:
Presidente - 1451883 - FABIO MENEGHETTI UGULINO DE ARAUJO
Interno - 2579664 - ALLAN DE MEDEIROS MARTINS
Externo ao Programa - 2757086 - JOILSON BATISTA DE ALMEIDA REGO
Externo à Instituição - EVANDRO DE BARROS COSTA - UFAL
Externo à Instituição - JOSE BEZERRA DE MENEZES FILHO - IFPB