Using Modelica models in real time dynamic optimization – gradient computation
Lars Imsland, Pål Kittilsen, Tor Steinar Schei · Linköping electronic conference proceedings · 2009
This paper reports on implementation of gradient computation for real-time dynamic optimization, where the dynamic models can be Modelica models.Analytical methods for gradient computation based on sensitivity integration is compared to finite difference-based methods.A case study reveals that analytical methods outperforms finite difference-methods as the number of inputs and/or input blocks increases.