Software Open Access
Lopes Junior, Enio;
Reinecke, Sebastian
{
"conceptrecid": "4567",
"owners": [
1035
],
"links": {
"badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.4987.svg",
"doi": "https://doi.org/10.14278/rodare.4987",
"conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.4567.svg",
"conceptdoi": "https://doi.org/10.14278/rodare.4567",
"bucket": "https://rodare.hzdr.de/api/files/5c732918-d2f8-4642-a0ec-dd4d543a52aa",
"html": "https://rodare.hzdr.de/record/4987",
"latest": "https://rodare.hzdr.de/api/records/5008",
"latest_html": "https://rodare.hzdr.de/record/5008"
},
"updated": "2026-10-01T10:44:36.367773+00:00",
"stats": {
"volume": 215908752.0,
"unique_downloads": 16.0,
"version_unique_downloads": 150.0,
"unique_views": 225.0,
"downloads": 16.0,
"version_unique_views": 3486.0,
"version_views": 3904.0,
"version_downloads": 187.0,
"version_volume": 1369417620.0,
"views": 240.0
},
"created": "2026-08-27T15:18:10.480267+00:00",
"doi": "10.14278/rodare.4987",
"id": 4987,
"conceptdoi": "10.14278/rodare.4567",
"files": [
{
"links": {
"self": "https://rodare.hzdr.de/api/files/5c732918-d2f8-4642-a0ec-dd4d543a52aa/hzdr/neural-mpcx-v3.1.1.zip"
},
"checksum": "md5:239655cd77a3201a178b756e5e96558b",
"bucket": "5c732918-d2f8-4642-a0ec-dd4d543a52aa",
"size": 13494297,
"key": "hzdr/neural-mpcx-v3.1.1.zip",
"type": "zip"
}
],
"metadata": {
"access_right": "open",
"version": "v3.1.1",
"keywords": [
"Neural Model Predictive Control",
"Recurrent Neural Networks",
"Long Short-Term Memory",
"RNN",
"LSTM",
"MPC",
"Nonlinear Model Predictive Control",
"Linear Model Predictive Control"
],
"resource_type": {
"title": "Software",
"type": "software"
},
"publication_date": "2026-08-27",
"description": "<p>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.</p>",
"title": "NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi",
"access_right_category": "success",
"creators": [
{
"affiliation": "Helmholtz-Zentrum Dresden-Rossendorf (HZDR)",
"name": "Lopes Junior, Enio",
"orcid": "0000-0002-7604-3205"
},
{
"affiliation": "Helmholtz-Zentrum Dresden-Rossendorf (HZDR)",
"name": "Reinecke, Sebastian",
"orcid": "0000-0003-2705-0692"
}
],
"doi": "10.14278/rodare.4987",
"license": {
"id": "Apache-2.0"
},
"pub_id": "43156",
"related_identifiers": [
{
"relation": "isSupplementTo",
"identifier": "https://github.com/hzdr/neural-mpcx/tree/v3.1.1",
"scheme": "url"
},
{
"relation": "isIdenticalTo",
"identifier": "https://www.hzdr.de/publications/Publ-43156",
"scheme": "url"
},
{
"relation": "isReferencedBy",
"identifier": "https://www.hzdr.de/publications/Publ-43756",
"scheme": "url"
},
{
"relation": "isVersionOf",
"identifier": "10.14278/rodare.4567",
"scheme": "doi"
}
],
"doc_id": "1",
"relations": {
"version": [
{
"count": 13,
"is_last": false,
"last_child": {
"pid_value": "5008",
"pid_type": "recid"
},
"parent": {
"pid_value": "4567",
"pid_type": "recid"
},
"index": 9
}
]
},
"communities": [
{
"id": "rodare"
},
{
"id": "topflow"
}
]
},
"revision": 17
}
| All versions | This version | |
|---|---|---|
| Views | 3,904 | 240 |
| Downloads | 187 | 16 |
| Data volume | 1.4 GB | 215.9 MB |
| Unique views | 3,486 | 225 |
| Unique downloads | 150 | 16 |