Contributions to Control Systems in the winter semester 2016/2017
In order to support the professional exchange in control and automation technology far beyond the borders of our university, some years ago a colloquium series with the name “Contributions to Control Systems” was brought into being at the Institute of Automatic Control. Speakers from industry and research talk about their work in relevant developments and applications in the field of automatic control.
All parties interested are very welcome.
We would be happy to add you to our corresponding email list. Please contact our office to be added.
Conference room of the IRT, Steinbachstr. 54, 52074 Aachen, Room 54A/202
Monday, January 16, 2017, 4:00pm
Innovations for the next Modelica Generation: modelling, simulation, regulation and optimization based on Julia
Professor Martin Otter
German Centre for Aviation and Space Travel
Institute for System Dynamics und Automatic Control
Friday, February 03, 2017, 10:00am
Operation and Maintenance Lessons Learned from a Parabolic Trough Concentrated Solar Power Plant
Dr. Astrid Hublitz
SLR STE SY EN CSY
91058 Erlangen, Germany
In Concentrated Solar Power Plants, solar radiation is concentrated to a receiver where heat is generated. This heat subsequently generates steam to drive a conventional thermal power plant cycle, generating electricity.
This presentation explains shortly concentrated solar power generation with parabolic trough collectors and focuses on the lessons learned from the operation of a 50 MWel CSP Parabolic Trough Plant in Spain.
Friday, February 10, 2017, 2:00pm
Herausforderungen des Betriebs von WindenergieanlagenRWTH
Dr.-Ing. Kirsten Theobald
Research & Development
Monday, March 20, 2017, 2:00pm
A Factor Graph Approach to Parameter Identiﬁcation for Afﬁne LPV Systems
Professor Philipp Rostalski
University of Lübeck
Institute for Electrical Engineering in Medicine
Factor graphs are a versatile graphical representation of factorizable functions. As a probabilistic graphical
model, they allow to visualize structured conditional independence, which can be exploited for solving inference problems by means of message passing along the nodes of the graph. In this article we present a novel factor graph formulation of the expectation maximization, called EM-based estimation technique for afﬁne linear parameter-varying system identiﬁcation. By extending the factor graph representation of the Kalman Filter/Smoother and the EM algorithm to parameter-varying matrices, a ﬂexible tool for nonlinear system identiﬁcation in the so-called linear parameter-varying, named LPV representation is obtained. Furthermore, a recursive reformulation of the algorithm suitable for tracking time-varying changes both accounted and
unaccounted for by a pre-deﬁned LPV system description is immediate from its factor graph-based formulation.