emedd33 / Reinforcement-Learning-in-Process-ControlLinks
Master thesis spring 2019. Template to be futher used by the department of chemical engineering at NTNU,
☆35Updated last year
Alternatives and similar repositories for Reinforcement-Learning-in-Process-Control
Users that are interested in Reinforcement-Learning-in-Process-Control are comparing it to the libraries listed below
Sorting:
- LSTM_MPC(reactive distillation system)☆11Updated 5 years ago
- SNU-EPEL / Integration-of-Reinforcement-Learning-and-Model-Predictive-Control-to-Optimize-Semi-batch-Bioreactor☆16Updated 3 years ago
- Codes for "Quantitative Comparison of Reinforcement Learning and Data-driven Model Predictive Control for Chemical and Biological Process…☆11Updated last year
- Deep Neural Network architecture as a predictive optimal controller for {HVAC+Solar cell + battery} disturbance afflicted system vs class…☆90Updated 6 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆91Updated 5 years ago
- Gaussian Process Regression Techniques - The source code corresponding to the Ph.D. thesis.☆71Updated 8 years ago
- ☆42Updated 2 years ago
- Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control☆56Updated 3 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆31Updated 2 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆78Updated last year
- Python code of the paper "Model structures and fitting criteria for system identification with neural networks" by Marco Forgione and Dar…☆21Updated 4 years ago
- Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…☆19Updated last year
- Approximate dynamic programming (ADP) and Policy gradient (PG) based sequential optimal experimental design (sOED)☆20Updated 3 years ago
- This is the code and data for the IEEE TPEL paper "Parameter Estimation of Power Electronic Converters with Physics-informed Machine Lear…☆68Updated 11 months ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆48Updated 4 years ago
- ☆45Updated 4 years ago
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆83Updated 6 years ago
- A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control☆151Updated 5 years ago
- ☆33Updated 2 years ago
- Control with Deep Reinforcement Learning☆15Updated 2 years ago
- Variable Time Reconstruction based modeling framework for soft sensor development☆13Updated 5 years ago
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆145Updated 2 years ago
- Accompanying repository for our work "On the relationship between data-enabled predictive control and subspace predictive control".☆23Updated 2 years ago
- This study explores using RL for CSTR control, assessing effectiveness vs. traditional controllers (PID, MPC). RL learns optimal behavior…☆18Updated last year
- Code accompanying the paper "Learning neural state-space models: do we need a state estimator?"☆10Updated 2 years ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆122Updated last year
- A collection of papers and code on fuel cell techniques and its application in distributed energy systems and mobility.☆27Updated 3 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆33Updated 2 years ago
- Learning-Based Efficient Approximation of Data-Enabled Predictive Control☆14Updated last year
- ☆93Updated 5 years ago