Neural network self tuning pi control for thin McKibben muscles in an antagonistic pair configuration
This paper proposes a model free neural network self-tuning proportional integral (NNPI) controller for a biceps-triceps thin McKibben muscle (TMM) platform in an antagonistic pair configuration. The study intends to explore the proposed model independent control strategy for TMMs in an antagonistic...
Saved in:
Main Authors: | Abdul Hafidz, Muhamad Hazwan, Mohd. Faudzi, Ahmad Athif, Jamaludin, Mohd. Najeb, Norsahperi, Nor Mohd. Haziq |
---|---|
Format: | Conference or Workshop Item |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/98615/ http://dx.doi.org/10.1007/978-3-030-97672-9_9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Neural network self tuning PI control for thin McKibben muscles in an antagonistic pair configuration
by: Abdul Hafidz, Muhamad Hazwan, et al.
Published: (2022) -
Control of thin McKibben muscles in an antagonistic pair configuration
by: Abdul Hafidz, Muhamad Hazwan, et al.
Published: (2022) -
Feasibility of PI control for a double-acting cylinder actuated by McKibben muscles
by: Mhd. Yusoff, Mohd. Akmal, et al.
Published: (2021) -
Simple neural network compact form model-free adaptive controller for thin McKibben muscle system
by: Abdul Hafidz, Muhamad Hazwan, et al.
Published: (2022) -
Switching model predictive control for thin McKibben muscle servo actuator
by: Mhd. Yusoff, Mohd. Akmal, et al.
Published: (2022)