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

DOI

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.

Identifier
DOI https://doi.org/10.14278/rodare.4601
Related Identifier IsSupplementTo https://github.com/hzdr/neural-mpcx/tree/v1.1.0
Related Identifier IsPartOf https://doi.org/10.14278/rodare.4567
Related Identifier IsPartOf https://rodare.hzdr.de/communities/rodare
Metadata Access https://rodare.hzdr.de/oai2d?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:rodare.hzdr.de:4601
Provenance
Creator Lopes-Júnior, Ênio ORCID logo; Reinecke, Sebastian Felix ORCID logo
Publisher Rodare
Publication Year 2026
Rights Apache License 2.0; Open Access; https://opensource.org/licenses/Apache-2.0; info:eu-repo/semantics/openAccess
OpenAccess true
Contact https://rodare.hzdr.de/support
Representation
Resource Type Software
Version v1.1.0
Discipline Life Sciences; Natural Sciences; Engineering Sciences