Conception of robust neural networks to improve hybrid control of an induction motor
Main Article Content
Abstract
Neural networks and fuzzy controllers are considered as the most efficient approximators of different functions and have also proved their capability of controlling nonlinear dynamical systems. So, in this paper, the authors introduce a novel technique of control called ‘hybrid control’ which is Based on Feedback Linearization and Field Oriented Control of an Induction Motor, in order to replace the sliding mode controllers (speed and flux ones). In fact, the objectives required by the introduction of neural networks, ‘RANNCs’ is to perform the control which is shown by simulation results.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
-
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
-
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
