Blar i NTNU Open på forfatter "Matias, José O.A."
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From-scratch development and improvement of a problem-based learning course: Nonlinear Model Predictive Control for Chemical and Biochemical Processes
Matias, José O.A.; Jäschke, Johannes (Journal article; Peer reviewed, 2022) -
Modifier adaptation for real-time optimization of a gas lifted well network
Matias, José O.A.; Le Roux, Galo AC; Jaeschke, Johannes (Journal article; Peer reviewed, 2018)This work studies the steady-state optimization of a Gas Lift Oil Well Network. The optimization approach used is based on the methodology proposed by (Gao et al., 2016), which is a Modifier Adaptation (MA) with gradient ... -
A regularized Moving Horizon Estimator for combined state and parameter estimation in a bioprocess experimental application
Tuveri, Andrea; Nakama, Caroline Satye Martins; Matias, José O.A.; Eng Holck, Haakon; Jäschke, Johannes; Imsland, Lars Struen; Bar, Nadav S (Peer reviewed; Journal article, 2023)Due to the lack or high costs of measurement devices to monitor and control metabolites in microbial cultivation processes, state estimators are often required. These estimators depend on available on-line measurements and ... -
Steady-state real-time optimization using transient measurements on an experimental rig
Matias, José O.A.; Oliveira, Julio P.C.; Le Roux, Galo A. C.; Jäschke, Johannes (Peer reviewed; Journal article, 2022)Real-time optimization with persistent parameter adaptation (ropa) is an rto approach, where the steady-state model parameters are updated dynamically using transient measurements. Consequently, we avoid waiting for a ... -
Using a neural network for estimating plant gradients in real-time optimization with modifier adaptation
Matias, José O.A.; Jäschke, Johannes (Journal article; Peer reviewed, 2019)In the presence of structural plant-model mismatch, standard real-time optimization (RTO) schemes are prone to compute an operation point that does not coincide with the plant optimum. Modifier Adaptation (MA) methods are ...