Version 1
: Received: 16 September 2018 / Approved: 17 September 2018 / Online: 17 September 2018 (11:39:35 CEST)
How to cite:
Camerino, M.; Pacheco, F. Neural Controller with Online Learning on Nonlinear System in a Cylindrical Tank. Preprints2018, 2018090305. https://doi.org/10.20944/preprints201809.0305.v1
Camerino, M.; Pacheco, F. Neural Controller with Online Learning on Nonlinear System in a Cylindrical Tank. Preprints 2018, 2018090305. https://doi.org/10.20944/preprints201809.0305.v1
Camerino, M.; Pacheco, F. Neural Controller with Online Learning on Nonlinear System in a Cylindrical Tank. Preprints2018, 2018090305. https://doi.org/10.20944/preprints201809.0305.v1
APA Style
Camerino, M., & Pacheco, F. (2018). Neural Controller with Online Learning on Nonlinear System in a Cylindrical Tank. Preprints. https://doi.org/10.20944/preprints201809.0305.v1
Chicago/Turabian Style
Camerino, M. and Filipe Pacheco. 2018 "Neural Controller with Online Learning on Nonlinear System in a Cylindrical Tank" Preprints. https://doi.org/10.20944/preprints201809.0305.v1
Abstract
Most systems that are the subject of control engineering studies have some non-linearity. An example of this is the horizontal cylindrical tank, commonly used in process industries. To deal with cases like this, several control theories have been developed over time, each one presenting better results in certain systems. This work presents an alternative for the control of nonlinear systems, without necessary modeling or previous information about the system, based on a new optimization law for the artificial neural network training in real time.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.