Publication detail

Neural Network-Based Semi-Inverse Controller

Schmidt, M., Pivoňka, P.

Original Title

Neural Network-Based Semi-Inverse Controller

English Title

Neural Network-Based Semi-Inverse Controller

Type

conference paper

Language

en

Original Abstract

The neural network-based semi-inverse controller is similar to an inverse controller. The inverse controller uses an inverse model of the controlled plant. Instead, the semi-inverse controller is based on a forward model. This avoids some of the problems of inversion. The control algorithm can work with a short sampling period and is suitable for real-time implementation in a PLC.

English abstract

The neural network-based semi-inverse controller is similar to an inverse controller. The inverse controller uses an inverse model of the controlled plant. Instead, the semi-inverse controller is based on a forward model. This avoids some of the problems of inversion. The control algorithm can work with a short sampling period and is suitable for real-time implementation in a PLC.

Keywords

Neural network, semi-inverse controller

RIV year

2006

Released

15.11.2006

Publisher

DAAAM International Vienna

Location

Vídeň

ISBN

3-901509-57-7

Book

Annals of DAAAM for 2006 & Proceedings

Pages from

367

Pages to

368

Pages count

2

BibTex


@inproceedings{BUT24394,
  author="Michal {Schmidt} and Petr {Pivoňka}",
  title="Neural Network-Based Semi-Inverse Controller",
  annote="The neural network-based semi-inverse controller is similar to an inverse controller. The inverse controller uses an inverse model of the controlled plant. Instead, the semi-inverse
controller is based on a forward model. This avoids some of the problems of inversion. The control algorithm can work with a short sampling period and is suitable for real-time implementation in a PLC.",
  address="DAAAM International Vienna",
  booktitle="Annals of DAAAM for 2006 & Proceedings",
  chapter="24394",
  institution="DAAAM International Vienna",
  year="2006",
  month="november",
  pages="367",
  publisher="DAAAM International Vienna",
  type="conference paper"
}