Ersü, Enis ; Tolle, Henning (2023)
A New Concept for Learning Control Inspired by Brain Theory.
In: IFAC Proceedings Volumes, 1984, 17 (2)
doi: 10.26083/tuprints-00023398
Article, Secondary publication, Publisher's Version
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| Item Type: | Article |
|---|---|
| Type of entry: | Secondary publication |
| Title: | A New Concept for Learning Control Inspired by Brain Theory |
| Language: | English |
| Date: | 2023 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | 1984 |
| Publisher: | IFAC - International Federation of Automatic Control |
| Journal or Publication Title: | IFAC Proceedings Volumes |
| Volume of the journal: | 17 |
| Issue Number: | 2 |
| DOI: | 10.26083/tuprints-00023398 |
| Corresponding Links: | |
| Origin: | Secondary publication service |
| Abstract: | The paper explains an unconventional learning control method based on assumptions in the literature about human problem solving and information storage in neuronal networks. The on-line learning comprises two stages: The dynamic input-output behaviour of the process to be controlled is stored stepwise in a neuron-like manner into an associative memory as a predictive process model, the control strategy planned via this model by optimization of a goal oriented performance index is then trained in the same way into a second associative memory. As a general mapping the learned behaviour is in both cases in general nonlinear, and by this such a control design is especially suited for strongly nonlinear processes. Simulations demonstrate the applicability of the new control concept. |
| Uncontrolled Keywords: | Associative memory systems, adaptive control, artificial intelligence, biocyberaetics, brain models, learning systems, neuronal networks, nonlinear control |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-233980 |
| Additional Information: | Zugl. Konferenzveröffentlichung: 9th IFAC World Congress: A Bridge Between Control Science and Technology, 02.-06.07.1984, Budapest, Hungary |
| Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
| Divisions: | 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems |
| Date Deposited: | 28 Apr 2023 08:26 |
| Last Modified: | 06 Jul 2023 11:34 |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23398 |
| PPN: | 509301266 |
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