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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wenger, M. Hametner, R. Zoitl, A. Voigt, A. |
| Copyright Year | 2011 |
| Description | Author affiliation: Vienna University of Technology, Automation and Control Institute, Gusshausstrasse 27-29 / E376, 1040 Vienna, Austria (Wenger, M.; Hametner, R.; Zoitl, A.) || VOIGT+WIPP Engineers GmbH, Märzstrasse 120, 1150 Vienna, Austria (Voigt, A.) |
| Abstract | Operating industrial plants at their maximum energy and resources efficiency often means to operate them close at their design limits. Due to strict safety and process parameter constraints, it is challenging to control them close to the optimal setpoints. Currently process performance improvement projects are realized by application of PC based model predictive controllers as add-ons. Applications of up-to-date optimizing control algorithms are characterized by high requirements on software architecture, numerical computing power and realtime behavior. These requirements are not accomplishable running optimizing control algorithms on Programmable Logic Controllers (PLCs) by current available software architectures. Therefore the aim of the Embedded Energy Efficiency Industrial Controller Platform (E3ICP) project is the development of an infrastructure for running state-of-the-art model predictive controllers on industrial embedded PLCs. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 227038 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457700170 |
| ISSN | 19460759 |
| e-ISBN | 9781457700187 |
| e-ISBN | 9781457700163 |
| DOI | 10.1109/ETFA.2011.6059212 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-05 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | IEC standards Mathematical model Predictive models Optimization Automation Process control Software |
| Content Type | Text |
| Resource Type | Article |
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