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
(16.1 MB)
| Name | Size | |
|---|---|---|
|
hzdr/neural-mpcx-v3.1.4.zip
md5:95a4297a75602b2ebd38f9efed99ee23 |
16.1 MB | Download |
3,556
159
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 3,556 | 281 |
| Downloads | 159 | 14 |
| Data volume | 1.2 GB | 225.6 MB |
| Unique views | 3,141 | 272 |
| Unique downloads | 122 | 13 |
Available in
- Publication date:
- September 8, 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/v3.1.4 - Communities:
- License (for files):
- Apache License 2.0