| Name | agentlib-mpc JSON |
| Version |
0.6.4
JSON |
| download |
| home_page | None |
| Summary | Framework for development and execution of agents for control and simulation of energy systems. |
| upload_time | 2024-12-17 13:31:07 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | BSD-3-Clause |
| keywords |
agents
mpc
control
distributed
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# agentlib_mpc
[](https://opensource.org/licenses/BSD-3-Clause)
[](https://rwth-ebc.github.io/AgentLib-MPC/main/pylint/pylint.html)
[](https://rwth-ebc.github.io/AgentLib-MPC/main/docs/index.html)
This is a plugin for [AgentLib](https://github.com/RWTH-EBC/AgentLib).
Includes functions for modeling with [CasADi](https://web.casadi.org/), and using those models in nonlinear MPC, central and distributed (based on ADMM).
See examples and the tutorial in the docs.
Best example to start is an MPC for [a single air conditioned room](https://github.com/RWTH-EBC/AgentLib-MPC/blob/main/examples/one_room_mpc/physical/simple_mpc.py).
## Installation
Install with:
```
pip install agentlib_mpc
```
To install with full dependencies (recommended), run:
```
pip install agentlib_mpc[full]
```
## Optional Dependencies
AgentLib_MPC has a number of optional dependencies:
- **fmu**: Support simulation of FMU models (https://fmi-standard.org/).
- **ml**: Use machine learning based NARX models for MPC. Currently supports neural networks, gaussian process regression and linear regression. Installs tensorflow, keras and scikit-learn.
- **interactive**: Utility functions for displaying mpc results in an interactive dashboard. Installs plotly and dash.
Install these like
````
pip install agentlib_mpc[ml]
````
## Citing AgentLib_MPC
For now, please cite the base framework under https://github.com/RWTH-EBC/AgentLib.
A preprint is available under http://dx.doi.org/10.2139/ssrn.4884846 and can be cited as:
> Eser, Steffen and Storek, Thomas and Wüllhorst, Fabian and Dähling, Stefan and Gall, Jan and Stoffel, Phillip and Müller, Dirk, A Modular Python Framework for Rapid Development of Advanced Control Algorithms for Energy Systems. Available at SSRN: https://ssrn.com/abstract=4884846 or http://dx.doi.org/10.2139/ssrn.4884846
When using AgentLib-MPC, please remember to cite other tools that you are using, for example CasADi or IPOPT.
## Acknowledgments
We gratefully acknowledge the financial support by Federal Ministry \\ for Economic Affairs and Climate Action (BMWK), promotional reference 03ET1495A.
<img src="./docs/source/images/BMWK_logo.png" alt="BMWK" width="200"/>
Raw data
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"description": "# agentlib_mpc\n[](https://opensource.org/licenses/BSD-3-Clause)\n[](https://rwth-ebc.github.io/AgentLib-MPC/main/pylint/pylint.html)\n[](https://rwth-ebc.github.io/AgentLib-MPC/main/docs/index.html)\n\nThis is a plugin for [AgentLib](https://github.com/RWTH-EBC/AgentLib). \nIncludes functions for modeling with [CasADi](https://web.casadi.org/), and using those models in nonlinear MPC, central and distributed (based on ADMM).\n\nSee examples and the tutorial in the docs.\nBest example to start is an MPC for [a single air conditioned room](https://github.com/RWTH-EBC/AgentLib-MPC/blob/main/examples/one_room_mpc/physical/simple_mpc.py).\n\n\n## Installation\n\nInstall with:\n\n```\npip install agentlib_mpc\n```\n\nTo install with full dependencies (recommended), run:\n```\npip install agentlib_mpc[full]\n```\n\n\n\n## Optional Dependencies\nAgentLib_MPC has a number of optional dependencies:\n \n - **fmu**: Support simulation of FMU models (https://fmi-standard.org/).\n - **ml**: Use machine learning based NARX models for MPC. Currently supports neural networks, gaussian process regression and linear regression. Installs tensorflow, keras and scikit-learn.\n - **interactive**: Utility functions for displaying mpc results in an interactive dashboard. Installs plotly and dash.\n\nInstall these like \n````\npip install agentlib_mpc[ml]\n````\n\n\n## Citing AgentLib_MPC\n\nFor now, please cite the base framework under https://github.com/RWTH-EBC/AgentLib.\n\nA preprint is available under http://dx.doi.org/10.2139/ssrn.4884846 and can be cited as: \n\n> Eser, Steffen and Storek, Thomas and W\u00fcllhorst, Fabian and D\u00e4hling, Stefan and Gall, Jan and Stoffel, Phillip and M\u00fcller, Dirk, A Modular Python Framework for Rapid Development of Advanced Control Algorithms for Energy Systems. Available at SSRN: https://ssrn.com/abstract=4884846 or http://dx.doi.org/10.2139/ssrn.4884846 \n\nWhen using AgentLib-MPC, please remember to cite other tools that you are using, for example CasADi or IPOPT.\n\n## Acknowledgments\n\nWe gratefully acknowledge the financial support by Federal Ministry \\\\ for Economic Affairs and Climate Action (BMWK), promotional reference 03ET1495A.\n\n<img src=\"./docs/source/images/BMWK_logo.png\" alt=\"BMWK\" width=\"200\"/>\n",
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