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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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{
  "title": "NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi", 
  "DOI": "10.14278/rodare.4601", 
  "author": [
    {
      "family": "Lopes-J\u00fanior, \u00canio"
    }, 
    {
      "family": "Reinecke, Sebastian Felix"
    }
  ], 
  "version": "v1.1.0", 
  "id": "4601", 
  "publisher": "Rodare", 
  "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.", 
  "issued": {
    "date-parts": [
      [
        2026, 
        4, 
        10
      ]
    ]
  }, 
  "type": "article"
}
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Publication date:
April 10, 2026
DOI:
10.14278/rodare.4601

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https://github.com/hzdr/neural-mpcx/tree/v1.1.0
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License (for files):
Apache License 2.0

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Version v1.1.0 10.14278/rodare.4601 Apr 10, 2026
Version v1.0.0 10.14278/rodare.4568 Mar 20, 2026
Cite all versions? You can cite all versions by using the DOI 10.14278/rodare.4567. This DOI represents all versions, and will always resolve to the latest one. Read more.

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