Simple Neural Network Compact Form Model-Free Adaptive Controller for Thin McKibben Muscle System-Reference-Cited by-同舟云学术

Simple Neural Network Compact Form Model-Free Adaptive Controller for Thin McKibben Muscle System

Published:2022 Issue: Volume:10 Page:123410-123422
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hafidz Muhamad Hazwan Abdul¹^ORCID,Faudzi Ahmad Athif Mohd¹^ORCID,Norsahperi Nor Mohd Haziq²^ORCID,Jamaludin Mohd Najeb³,Hamid Dayang Tiawa Awang⁴,Mohamaddan Shahrol⁵

Affiliation:

1. Faculty of Engineering, School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

2. Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia

3. Sports Innovation and Technology Centre, Institute Human Centered Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

4. Faculty of Islamic Technology, Sultan Sharif Ali Islamic University, Bandar Seri Begawan, Brunei

5. Department of Bioscience and Engineering, College of Systems Engineering and Science, Shibaura Institute of Technology, Saitama, Japan

Funder

Ministry of Higher Education Malaysia (MOHE) through Fundamental Research Grant Scheme

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/ielx7/6287639/9668973/09934849.pdf?arnumber=9934849

Reference32 articles.

1. The comparison of optimizing SVM by GA and grid search

2. Particle swarm-based and neuro-based FOPID controllers for a Twin Rotor System with improved tracking performance and energy reduction

3. Research on PSA-MFAC for a novel bionic elbow joint system actuated by pneumatic artificial muscles

4. Filtering-Error Constrained Angle Tracking Adaptive Learning Fuzzy Control for Pneumatic Artificial Muscle Systems Under Nonzero Initial Errors

5. Adaptive control for a motion mechanism with pneumatic artificial muscles subject to dead-zones

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