Application of Mixture of Experts in Machine Learning-Based Controlling of DC-DC Power Electronics Converter-Reference-Cited by-同舟云学术

Application of Mixture of Experts in Machine Learning-Based Controlling of DC-DC Power Electronics Converter

Published:2022 Issue: Volume:10 Page:117157-117169
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mohammadzadeh Mohsen¹,Akbari Ehsan²^ORCID,Salameh Anas A.³,Ghadamyari Mojtaba⁴,Pirouzi Sasan⁵,Senjyu Tomonobu⁶^ORCID

Affiliation:

1. Faculty of Electrical and Computer Engineering, Noshirvani University of Technology, Babol, Iran

2. Department of Electrical Engineering, Mazandaran University of Science and Technology, Babol, Iran

3. Department of Management Information Systems, College of Business Administration, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia

4. Department of Computer Engineering, Lebanese French University, Kurdistan Region, Iraq

5. Power System Group, Semirom Branch, Islamic Azad University, Semirom, Iran

6. Faculty of Engineering, University of the Ryukyus, Okinawa, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09933741.pdf?arnumber=9933741

Reference58 articles.

1. Active Current Sharing of a Parallel DC-DC Converters System Using Bat Algorithm Optimized Two-DOF PID Control

2. A Novel Nonlinear Deep Reinforcement Learning Controller for DC–DC Power Buck Converters

3. A simplified Mixed Logical Dynamic model and Model Predictive Control of Boost converter with current reference compensator

4. Hybrid modeling and control of a DC-DC boost converter via Extended Mixed Logical Dynamical systems (EMLDs)

5. Explicit model predictive control of quadratic boost converter for high step-up applications;prabhu;Proc IEEE Int Conf Power Electron Drives Energy Syst (PEDES),2018

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