| Methodology for detecting model–plant mismatches affecting model predictive control performance V Botelho, JO Trierweiler, M Farenzena, R Duraiski Industrial & Engineering Chemistry Research 54 (48), 12072-12085, 2015 | 47 | 2015 |
| Perspectives and challenges in performance assessment of model predictive control V Botelho, JO Trierweiler, M Farenzena, R Duraiski The Canadian Journal of Chemical Engineering 94 (7), 1225-1241, 2016 | 21 | 2016 |
| Diagnosis of Poor Performance in Model Predictive Controllers: Unmeasured Disturbance versus Model–Plant Mismatch V Botelho, JO Trierweiler, M Farenzena Industrial & Engineering Chemistry Research 55 (44), 11566-11582, 2016 | 15 | 2016 |
| Assessment of model-plant mismatch by the nominal sensitivity function for unconstrained MPC VR Botelho, JO Trierweiler, M Farenzena, R Duraiski IFAC-PapersOnLine 48 (8), 753-758, 2015 | 11 | 2015 |
| A new approach for practical identifiability analysis applied to dynamic phenomenological models VR Botelho, LF Trierweiler, JO Trierweiler IFAC Proceedings Volumes 45 (15), 691-696, 2012 | 10 | 2012 |
| Model assessment of MPCs with control ranges: An industrial application in a delayed coking unit VR Botelho, JO Trierweiler, M Farenzena, LGS Longhi, AC Zanin, ... Control Engineering Practice 84, 261-273, 2019 | 8 | 2019 |
| MPC Model assessment of highly coupled systems V Botelho, JO Trierweiler, M Farenzena Industrial & Engineering Chemistry Research 55 (50), 12880-12895, 2016 | 8 | 2016 |
| Parameter estimation of models with limit cycle based on the reformulation of the objective function A Apio, VR Botelho, JO Trierweiler Computers & Chemical Engineering 109, 236-248, 2018 | 7 | 2018 |
| Model Performance Assessment of a Predictive Controller for Propylene/Propane Separation ÉRP Claro, V Botelho, JO Trierweiler, M Farenzena IFAC-PapersOnLine 49 (7), 978-983, 2016 | 7 | 2016 |
| Estimation of kinetic parameters of a polymerization reactor using real data V Botelho, I de Souza Moreira, JO Trierweiler, GA Neumann, ... IFAC Proceedings Volumes 45 (15), 685-690, 2012 | 5 | 2012 |
| Locating poor models in MPC applications ÉRP Claro, D de Oliveira Francisco, VR Botelho, M Farenzena, ... Computers & Chemical Engineering 130, 106545, 2019 | 4 | 2019 |
| Estudo comparativo de metodologias para avaliação de modelos de controladores preditivos aplicadas a uma unidade de coqueamento retardado (comparative study of methods for … VR Botelho, JO Trierweiler, M Farenzena, LGS Longhi, AC Zanin, ... Engevista 17 (4), 463-476, 2015 | 4 | 2015 |
| Auditoria e diagnóstico de modelos para controladores preditivos industriais VR Botelho | 3 | 2015 |
| Channel oriented approach for multivariable model updating using historical data JO Trierweiler, D de Oliveira Francisco, VR Botelho, M Farenzena Computers & Chemical Engineering 143, 107085, 2020 | 2 | 2020 |
| Desafios E Perspectivas Na Auditoria De Mpcs VR BOTELHO, JO TRIERWEILER, M FARENZENA, GH MÜLLER no. February, 11422-11429, 2015 | 2 | 2015 |
| Interpreting convolutional neural networks for brain tumor classification: An explainable artificial intelligence approach DEB Schiavon, CDL Becker, VR Botelho, TA Pianoski Brazilian Conference on Intelligent Systems, 77-91, 2023 | 1 | 2023 |
| MPC model monitoring and diagnosis for non-square systems V Botelho, JO Trierweiler, M Farenzena Journal of Process Control 97, 26-44, 2021 | 1 | 2021 |
| Nova metodologia para análise de identificabilidade e estimação de parâmetros de modelos fenomenológicos VR Botelho | 1 | 2012 |
| AQMI: Software for assessing the quality of mammographic images AD Mangussi, TA Pianoschi, B Cecchetto, VR Botelho Brazilian Journal of Radiation Sciences 11 (3), 1-16, 2023 | | 2023 |
| Modeling of the mass attenuation coefficients of X ray beams using deep neural networks (DNN) and NIST database GB DA SILVA, VR BOTELHO, CDL Becker, C Viccari, TA Pianoschi Brazilian Journal of Radiation Sciences 11 (1A (Suppl.)), 1-20, 2023 | | 2023 |
