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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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).
Submitted. Physics-Informed Neural Networks with Skip Connections for Modeling and Control of Gas-Lifted Oil Wells.
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2024. Physics-Informed Neural Nets for Control of Dynamical Systems. Neurocomputing. 579 (1014.48 KB)
(1014.48 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).
2022. Nonlinear Model Predictive Control of Electrical Submersible Pumps based on Echo State Networks . Advanced Engineering Informatics. 52 (633.48 KB)
(633.48 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).
2023. Investigation of Proper Orthogonal Decomposition for Echo State Networks. Neurocomputing. :126395. (555.51 KB)
(555.51 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)