Evolutionary fuzzy system for architecture control in a constructive neural network
- Rodrigo Calvo, M. Figueiredo, Eric A. Antonelo
- Computer ScienceInternational Symposium on Computational…
- 27 June 2005
An evolutionary system to control the growth of a constructive neural network for autonomous navigation is described and the efficiency of the classifier fuzzy system for analyzing if it is worth inserting a new neuron into the architecture is shown.
Physics-Informed Neural Nets-based Control
- Eric A. Antonelo, E. Camponogara, L. O. Seman, Eduardo Rehbein de Souza, J. Jordanou, Jomi F. Hubner
- Computer ScienceArXiv
- 2021
This work presents a new framework called Physics-Informed Neural Nets-based Control (PINC), which proposes a novel PINN-based architecture that is amenable to control problems and able to simulate for longer-range time horizons that are not fixed beforehand.
On Learning Navigation Behaviors for Small Mobile Robots With Reservoir Computing Architectures
- Eric A. Antonelo, B. Schrauwen
- Computer ScienceIEEE Transactions on Neural Networks and Learning…
- 1 April 2015
A general reservoir computing (RC) learning framework that can be used to learn navigation behaviors for mobile robots in simple and complex unknown partially observable environments and three learning approaches for navigation behaviors are shown.
Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing
- Eric A. Antonelo, B. Schrauwen, J. V. Campenhout
- Computer ScienceNeural Processing Letters
- 1 December 2007
This contribution shows that the recently emerged paradigm of Reservoir Computing (RC) is very well suited to solve all of the above mentioned problems, namely learning by example, robot localization, map and path generation.
Echo State Networks for Practical Nonlinear Model Predictive Control of Unknown Dynamic Systems
- J. Jordanou, Eric A. Antonelo, E. Camponogara
- EngineeringIEEE Transactions on Neural Networks and Learning…
- 28 December 2021
The ESN-PNMPC architecture is shown by application to the control of the four-tank system and an oil production platform, outperforming the predictive approach with a long-short term memory (LSTM) model, two standard linear control algorithms, and approximate predictive control.
Reservoir computing architectures for modeling robot navigation systems
- Eric A. Antonelo
- Computer Science
- 2011
Event detection and localization for small mobile robots using reservoir computing
- Eric A. Antonelo, B. Schrauwen, D. Stroobandt
- Computer ScienceNeural Networks
- 1 August 2008
Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells
- Eric A. Antonelo, E. Camponogara, B. Foss
- Computer ScienceNeural Networks
- 2017
Nonlinear Model Predictive Control of an Oil Well with Echo State Networks
- J. Jordanou, E. Camponogara, Eric A. Antonelo, M. A. Aguiar
- Engineering
- 2018
Online learning control with Echo State Networks of an oil production platform
- J. Jordanou, Eric A. Antonelo, E. Camponogara
- EngineeringEngineering applications of artificial…
- 1 October 2019
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