Publications
Key references
See my publications also at Google Scholar
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2024. Physics-Informed Neural Nets for Control of Dynamical Systems. Neurocomputing. 579
(1014.48 KB)
(1014.48 KB) .
2015. On Learning Navigation Behaviors for Small Mobile Robots With Reservoir Computing Architectures. IEEE Transactions on Neural Networks and Learning Systems. 26:763-780. (5.14 MB)
(5.14 MB) .
2012. Learning Slow Features with Reservoir Computing for Biologically-inspired Robot Localization. Neural Networks. 25:178-190. (2.77 MB)
(2.77 MB) .
2011. Reservoir Computing Architectures for Modeling Robot Navigation Systems. (21.33 MB)
(21.33 MB) .
2007. Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing. Neural Processing Letters. 26:233–249. (8.43 MB)
(8.43 MB) Export 5 results:
Author Title Type [ Year
] Filters: Author is Eduardo Camponogara [Clear All Filters]
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2024. Physics-Informed Neural Nets for Control of Dynamical Systems. Neurocomputing. 579 (1014.48 KB)
(1014.48 KB).
2024. Physics-Informed Neural Networks with Skip Connections for Modeling and Control of Gas-Lifted Oil Wells. Applied Soft Computing. 158 (1.83 MB)
(1.83 MB).
2023. Investigation of Proper Orthogonal Decomposition for Echo State Networks. Neurocomputing. :126395. (555.51 KB)
(555.51 KB).
2022. Nonlinear Model Predictive Control of Electrical Submersible Pumps based on Echo State Networks . Advanced Engineering Informatics. 52 (633.48 KB)
(633.48 KB).
2019. Online Learning Control with Echo State Networks of an Oil Production Platform. Engineering Applications of Artificial Intelligence. 85:214-228. (512.33 KB)
(512.33 KB).
2018. Nonlinear Model Predictive Control of an Oil Well with Echo State Networks. IFAC-PapersOnLine (3rd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production OOGP 2018). 51:13-18. (386.53 KB)
(386.53 KB).
2017. Echo State Networks for Data-driven Downhole Pressure Estimation in Gas-lift Oil Wells. Neural Networks. 85:106-117. (913.18 KB)
(913.18 KB).
2017. Recurrent Neural Network based control of an Oil Well. XIII Brazilian Symposium on Intelligent Automation (SBAI). :924-931. (412.17 KB)
(412.17 KB).
2015. An Echo State Network-based Soft Sensor of Downhole Pressure for a Gas-lift Oil Well. 16th International Conference on Engineering Applications of Neural Networks. Communications in Computer and Information Science, vol 517:379-389. (1010.5 KB)
(1010.5 KB).
2015. System Identification of a Vertical Riser Model with Echo State Networks. IFAC-PapersOnLine (2nd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production). 48(6):304-310. (549.4 KB)
(549.4 KB)