Robust Adaptive Neural Network Tracking Control With Optimized Super-Twisting Sliding-Mode Technique for Induction Motor Drive System-Reference-Cited by-同舟云学术

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Robust Adaptive Neural Network Tracking Control With Optimized Super-Twisting Sliding-Mode Technique for Induction Motor Drive System

Published:2022-05 Issue:3 Volume:58 Page:4134-4157
ISSN:0093-9994
Container-title:IEEE Transactions on Industry Applications
language:
Short-container-title:IEEE Trans. on Ind. Applicat.

Author:

El-Sousy Fayez F. M.¹^ORCID,Amin Mahmoud M.²^ORCID,Mohammed Osama A.³^ORCID

Affiliation:

1. Department of Electrical Engineering, Prince Sattam bin Abdulaziz University, Al Kharj, Saudi Arabia

2. Department of Electrical and Computer Engineering, Riverdale, NY, USA

3. Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA

Funder

Deputyship for Research and Innovation

Ministry of Education in Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/28/9778222/09739903.pdf?arnumber=9739903

Reference81 articles.

1. Logistic Regression by Means of Evolutionary Radial Basis Function Neural Networks

2. PREDICTION OF PARKINSON'S DISEASE TREMOR ONSET USING A RADIAL BASIS FUNCTION NEURAL NETWORK BASED ON PARTICLE SWARM OPTIMIZATION

3. Evolutionary Optimization of Radial Basis Function Classifiers for Data Mining Applications

4. Evolutionary artificial neural networks by multi-dimensional particle swarm optimization

5. A growing and pruning sequential learning algorithm of hyper basis function neural network for function approximation

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