Software Open Access
Lopes-Júnior, Ênio;
Reinecke, Sebastian Felix
{
"version": "v3.1.3",
"@type": "SoftwareSourceCode",
"@context": "https://schema.org/",
"datePublished": "2026-09-02",
"@id": "https://doi.org/10.14278/rodare.4991",
"name": "NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi",
"license": "https://opensource.org/licenses/Apache-2.0",
"description": "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.",
"url": "https://rodare.hzdr.de/record/4991",
"creator": [
{
"affiliation": "Helmholtz-Zentrum Dresden-Rossendorf (HZDR)",
"@type": "Person",
"name": "Lopes-J\u00fanior, \u00canio",
"@id": "https://orcid.org/0000-0002-7604-3205"
},
{
"affiliation": "Helmholtz-Zentrum Dresden-Rossendorf (HZDR)",
"@type": "Person",
"name": "Reinecke, Sebastian Felix",
"@id": "https://orcid.org/0000-0003-2705-0692"
}
],
"identifier": "https://doi.org/10.14278/rodare.4991",
"codeRepository": "https://github.com/hzdr/neural-mpcx/tree/v3.1.3"
}
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| Unique downloads | 55 | 1 |