Echtzeit-Implementierung von NMPC

Prädiktive Regelung für mechatronische Systeme unter Verwendung eines hybriden Modells

Autor/innen

  • Stefan Löw
  • Dragan Obradovic Siemens

DOI:

https://doi.org/10.17560/atp.v60i08.2359

Schlagworte:

Modellprädiktive Regelung, NMPC, Real-time Iteration, Neuronale Netze, Hybrides Modell, Windturbine

Abstract

Nonlinear Model Predictive Control (NMPC) is an aspiring control method for the implementation of advanced controller behavior. The present work shows the symbolic math implementation of a mechatronic system model containing aerodynamic nonlinearities modeled by Feedforward Neural Networks. Gradients for the optimization are obtained efficiently by exploiting the feedforward property of the Neural Networks and symbolic computation. Current research on the implementation of damage metrics into the cost function is stated briefly. In order to achieve real-time capability, the method Real-time Iteration is used.

Literaturhinweise

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Veröffentlicht

20.08.2018

Ausgabe

Rubrik

Hauptbeitrag / Peer-Review