Software Open Access
NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi
Lopes-Júnior, Ênio;
Reinecke, Sebastian Felix
Citation Style Language JSON Export
{
"type": "article",
"publisher": "Rodare",
"id": "4991",
"title": "NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi",
"DOI": "10.14278/rodare.4991",
"issued": {
"date-parts": [
[
2026,
9,
2
]
]
},
"abstract": "NeuralMPCX is a Python library for building and deploying Model Predictive Controllers with classic and neural dynamical models. You write constrained MPC with RNN/LSTM models in a CasADi/IPOPT workflow. The library handles CasADi RNN integration, warm-starting, constraint management, real-time feasibility, and both LTI state-space and neural dynamics in one framework. You can run neural and classical MPC controllers side by side.",
"author": [
{
"family": "Lopes-J\u00fanior, \u00canio"
},
{
"family": "Reinecke, Sebastian Felix"
}
],
"version": "v3.1.3"
}
1,912
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|---|---|---|
| Views | 1,912 | 13 |
| Downloads | 50 | 0 |
| Data volume | 48.4 MB | 0 Bytes |
| Unique views | 1,713 | 13 |
| Unique downloads | 40 | 0 |
Available in
- Publication date:
- September 2, 2026
- DOI:
-
- Related identifiers:
- Supplement to:
https://github.com/hzdr/neural-mpcx/tree/v3.1.3 - Communities:
- License (for files):
- Apache License 2.0