56 citations · 267 across the 15 of their papers we have counts for
9 papers · 1 filter
Nonlinearity Compensation Based on Identified NARX Polynomials Models
Lucas A. Tavares, Petrus E. O. G. B. Abreu, Luis A. Aguirre
This paper deals with the compensation of nonlinearities in dynamical systems using nonlinear polynomial autoregressive models with exogenous inputs (NARX). The compensation approa…
Identification of NARX Models for Compensation Design
Lucas A. Tavares, Petrus E. O. G. B. Abreu, Luis A. Aguirre
This report presents the modeling results for three systems, two numerical and one experimental. In the numerical examples, we use mathematical models previously obtained in the li…
Including steady-state information in nonlinear models: an application to the development of soft-sensors
Leandro Freitas, Bruno H. G. Barbosa, Luis A. Aguirre
When the dynamical data of a system only convey dynamic information over a limited operating range, the identification of models with good performance over a wider operating range…
Identification and nonlinearity compensation of hysteresis using NARX models
Petrus E. O. G. B. Abreu, Lucas A. Tavares, Bruno O. S. Teixeira +1
This paper deals with two problems: the identification and compensation of hysteresis nonlinearity in dynamical systems using nonlinear polynomial autoregressive models with exogen…
Multi-objective Evolutionary Approach to Grey-Box Identification of Buck Converter
Faizal Hafiz, Akshya Swain, Eduardo M. A. M. Mendes +1
The present study proposes a simple grey-box identification approach to model a real DC-DC buck converter operating in continuous conduction mode. The problem associated with the i…
A Bird's Eye View of Nonlinear System Identification
Luis Antonio Aguirre
This text aims at providing a bird's eye view of system identification with special attention to nonlinear systems. The driving force is to give a feeling for the philosophical pro…
On the smoothness of nonlinear system identification
Antônio H. Ribeiro, Koen Tiels, Jack Umenberger +2
We shed new light on the \textit{smoothness} of optimization problems arising in prediction error parameter estimation of linear and nonlinear systems. We show that for regions of…
Lasso Regularization Paths for NARMAX Models via Coordinate Descent
Antônio H. Ribeiro, Luis A. Aguirre
We propose a new algorithm for estimating NARMAX models with regularization for models represented as a linear combination of basis functions. Due to the -norm penalty t…
"Parallel Training Considered Harmful?": Comparing series-parallel and parallel feedforward network training
Antônio H. Ribeiro, Luis A. Aguirre
Neural network models for dynamic systems can be trained either in parallel or in series-parallel configurations. Influenced by early arguments, several papers justify the choice o…