Software Open Access
Lopes-Júnior, Ênio;
Reinecke, Sebastian Felix
{
"title": "NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi",
"type": "article",
"author": [
{
"family": "Lopes-J\u00fanior, \u00canio"
},
{
"family": "Reinecke, Sebastian Felix"
}
],
"version": "v3.0.1",
"id": "4739",
"publisher": "Rodare",
"DOI": "10.14278/rodare.4739",
"issued": {
"date-parts": [
[
2026,
6,
26
]
]
},
"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."
}
| All versions | This version | |
|---|---|---|
| Views | 835 | 14 |
| Downloads | 28 | 0 |
| Data volume | 10.3 MB | 0 Bytes |
| Unique views | 771 | 14 |
| Unique downloads | 27 | 0 |