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NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi

Lopes-Júnior, Ênio; Reinecke, Sebastian Felix

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{
  "publisher": "Rodare", 
  "abstract": "<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", 
  "DOI": "10.14278/rodare.4568", 
  "author": [
    {
      "family": "Lopes-J\u00fanior, \u00canio"
    }, 
    {
      "family": "Reinecke, Sebastian Felix"
    }
  ], 
  "type": "article", 
  "id": "4568", 
  "issued": {
    "date-parts": [
      [
        2026, 
        3, 
        20
      ]
    ]
  }, 
  "version": "v1.0.0"
}
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Publication date:
March 20, 2026
DOI:
10.14278/rodare.4568

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Identical to:
https://www.hzdr.de/publications/Publ-43156
Supplement to:
https://github.com/hzdr/neural-mpcx/tree/v1.0.0
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License (for files):
Apache License 2.0

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Version v1.0.0 10.14278/rodare.4568 Mar 20, 2026
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