56 citations · 267 across the 15 of their papers we have counts for
17 papers
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…
Particle filtering of dynamical networks: Highlighting observability issues
Arthur N. Montanari, Luis A. Aguirre
In a network of high-dimensionality, it is not feasible to measure every single node. Thus, an important goal in the literature is to define the optimal choice of sensor nodes that…
Structural, Dynamical and Symbolic Observability: From Dynamical Systems to Networks
Luis A. Aguirre, Leonardo L. Portes, Christophe Letellier
The concept of observability of linear systems initiated with Kalman in the mid 1950s. Roughly a decade later, the observability of nonlinear systems appeared. By such definitions…
A nonlinear graph-based theory for dynamical network observability
Christophe Letellier, Irene Sendiña-Nadal, Luis A. Aguirre
A faithful description of the state of a complex dynamical network would require, in principle, the measurement of all its variables, an infeasible task for systems with practi…
Mixed measurements and the detection of phase synchronization in networks
Leonardo L. Portes, Luis A. Aguirre
Multivariate singular spectrum analysis (M-SSA), with a varimax rotation of eigenvectors, was recently proposed to provide detailed information about phase synchronization in netwo…
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…
Control and Observability Aspects of Phase Synchronization
Luis Antonio Aguirre, Leandro Freitas
This paper addresses important control and observability aspects of the phase synchronization of two oscillators. To this aim a feedback control framework is proposed based on whic…
"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…
Observability and Synchronization of Neuron Models
Luis A. Aguirre, Leonardo L. Portes, Christophe Letellier
Observability is the property that enables to distinguish two different locations in -dimensional state space from a reduced number of measured variables, usually just one. In h…
Joint Maximum a Posteriori State Path and Parameter Estimation in Stochastic Differential Equations
Dimas Abreu Archanjo Dutra, Bruno Otávio Soares Teixeira, Luis Antonio Aguirre
In this article, we introduce the joint maximum a posteriori state path and parameter estimator (JME) for continuous-time systems described by stochastic differential equations (SD…
Maximum a Posteriori State Path Estimation: Discretization Limits and their Interpretation
Dimas Abreu Dutra, Bruno Otávio Soares Teixeira, Luis Antonio Aguirre
Continuous-discrete models with dynamics described by stochastic differential equations are used in a wide variety of applications. For these systems, the maximum a posteriori (MAP…