Johannes Jäschke

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 19

Top Topics

Predictive Control

Optimization Methods

Top Venues

Comput. Chem. Eng.

IEEE Control. Syst. Lett.

Publications

Evren Mert Turan, Johannes Jäschke
Closed-loop training of static output feedback neural network controllers for large systems: A distillation case study. CoRR (2024)
Zawadi Mdoe, Dinesh Krishnamoorthy, Johannes Jäschke
Stability Properties of the Adaptive Horizon Multi-Stage MPC. CoRR (2023)
Andrea Tuveri, Caroline S. M. Nakama, José Matias, Haakon Eng Holck, Johannes Jäschke, Lars Imsland, Nadav Bar
A regularized Moving Horizon Estimator for combined state and parameter estimation in a bioprocess experimental application. Comput. Chem. Eng. 172 (2023)
Simen Bjorvand, Johannes Jäschke
Improving Primal Decomposition for Multistage MPC Using an Extended Newton Method. IEEE Control. Syst. Lett. 7 (2023)
Evren Mert Turan, Zawadi Mdoe, Johannes Jäschke
Learning convex objectives to reduce the complexity of model predictive control. CoRR (2023)
Vinh Phuc Bui Nguyen, José Matias, Johannes Jäschke
Convolutional Neural Network as a Steady-state Detector for Real-time Optimization. ECC (2022)
Evren Mert Turan, Johannes Jäschke
Multiple Shooting for Training Neural Differential Equations on Time Series. IEEE Control. Syst. Lett. 6 (2022)
Timur Bikmukhametov, Johannes Jäschke
Hybrid Machine Learning Modeling of Engineering Systems - A Probabilistic Perspective Tested on a Multiphase Flow Modeling Case Study. CoRR (2022)
Xingheng Liu, José Matias, Johannes Jäschke, Jørn Vatn
Gibbs sampler for noisy Transformed Gamma process: Inference and remaining useful life estimation. Reliab. Eng. Syst. Saf. 217 (2022)
Mandar Thombre, Zhou (Joyce) Yu, Johannes Jäschke, Lorenz T. Biegler
Sensitivity-Assisted multistage nonlinear model predictive control: Robustness, stability and computational efficiency. Comput. Chem. Eng. 148 (2021)
Zawadi Mdoe, Dinesh Krishnamoorthy, Johannes Jäschke
Adaptive Horizon Multistage Nonlinear Model Predictive Control. ACC (2021)
Evren Mert Turan, Johannes Jäschke
Multiple shooting with neural differential equations. CoRR (2021)
José Matias, Johannes Jäschke
Online model maintenance in real-time optimization methods. Comput. Chem. Eng. 145 (2021)
Timur Bikmukhametov, Johannes Jäschke
Combining machine learning and process engineering physics towards enhanced accuracy and explainability of data-driven models. Comput. Chem. Eng. 138 (2020)
Krishnamoorthy Dinesh, Sigurd Skogestad, Johannes Jäschke
Multistage Model Predictive Control with Online Scenario Tree Update using Recursive Bayesian Weighting. ECC (2019)
Krishnamoorthy Dinesh, Eka Suwartadi, Bjarne Foss, Sigurd Skogestad, Johannes Jäschke
Improving Scenario Decomposition for Multistage MPC Using a Sensitivity-Based Path-Following Algorithm. IEEE Control. Syst. Lett. 2 (4) (2018)
Johannes Jäschke, Yi Cao, Vinay Kariwala
Self-optimizing control - A survey. Annu. Rev. Control. 43 (2017)
Tamal Das, Johannes Jäschke
Pathfollowing approach for a sensitivity based moving horizon estimator. CDC (2017)
Vyacheslav Kungurtsev, Johannes Jäschke
A Predictor-Corrector Path-Following Algorithm for Dual-Degenerate Parametric Optimization Problems. SIAM J. Optim. 27 (1) (2017)
Johannes Jäschke, Sigurd Skogestad
Optimal operation of heat exchanger networks with stream split: Only temperature measurements are required. Comput. Chem. Eng. 70 (2014)
Johannes Jäschke, Miroslav Fikar, Sigurd Skogestad
Self-optimizing invariants in dynamic optimization. CDC/ECC (2011)
Henrik Manum, Sigurd Skogestad, Johannes Jäschke
Convex initialization of the H2-optimal static output feedback problem. ACC (2009)
Johannes Jäschke, Helge Smedsrud, Sigurd Skogestad, Henrik Manum
Optimal operation of a waste incineration plant for district heating. ACC (2009)