Design of “Deep Learning Controller”
Köksal Erentürk1*, Saliha Erentürk2
1Department of E&E Engineering, College of Engineering, Ataturk University , Erzurum, Turkey
2Department of Chemical Engineering, College of Engineering, Ataturk University , Erzurum, Turkey
* Corresponding author: erenturk@yahoo.com
Presented at the Ist International Symposium on Innovative Approaches in Scientific Studies (ISAS 2018), Kemer-Antalya, Turkey, Apr 11, 2018
SETSCI Conference Proceedings, 2018, 2, Page (s): 134-134 , https://doi.org/
Published Date: 23 June 2018 |
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Abstract
Deep learning allows computational models of multiple processing layers to learn and represent data with multiple levels of abstraction mimicking how the brain perceives and understands multimodal information, thus implicitly capturing intricate structures of large‐ scale data. In the meantime, recent advances in deep learning, encompassing neural networks, hierarchical probabilistic models, and a variety of unsupervised and supervised feature learning algorithms, have brought about tremendous development to many areas of interest to the engineering community. In this study, a brief introduction for deep learning and its application on control engineering have been presented.
Keywords - Deep learning, controller design, control engineering, big data
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