Software Open Access
NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi
Lopes Junior, Enio;
Reinecke, Sebastian
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.
Files
(797.5 kB)
| Name | Size | |
|---|---|---|
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hzdr/neural-mpcx-v3.0.2.zip
md5:18375e0f7d1db79dbd9682423051774b |
797.5 kB | Download |
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| All versions | This version | |
|---|---|---|
| Views | 1,598 | 166 |
| Downloads | 48 | 3 |
| Data volume | 21.5 MB | 2.4 MB |
| Unique views | 1,472 | 154 |
| Unique downloads | 38 | 3 |
Available in
- Publication date:
- August 4, 2026
- DOI:
-
- Keyword(s):
- Neural Model Predictive Control Recurrent Neural Networks Long Short-Term Memory RNN LSTM MPC Nonlinear Model Predictive Control Linear Model Predictive Control
- Related identifiers:
- Identical to:
https://www.hzdr.de/publications/Publ-43156 - Referenced by:
https://www.hzdr.de/publications/Publ-43756 - Supplement to:
https://github.com/hzdr/neural-mpcx/tree/v3.0.2 - Communities:
- License (for files):
- Apache License 2.0