The identification and control of a finger exoskeleton for grasping rehabilitation

This paper evaluates the efficacy of different classical control architectures in performing grasping motion. The exoskeleton system was obtained via system identification method in which the input and output data was measured by means of current sensor (ACS712) and encoder attached to a DC geared m...

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Bibliographic Details
Main Authors: Zahari, Taha, Muhammad Muaz, Alim, Anwar, P. P. Abdul Majeed, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman, Mohd Ali Hanafiah, Shaharudin, M. H. A., Hassan
Other Authors: Mohd Hasnun Ariff, Hassan
Format: Book Section
Language:English
English
Published: Springer Singapore 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/21163/7/Identification%20and%20Control%20of%20a%20finger%20exoskeleton-fkp-2018-1.pdf
http://umpir.ump.edu.my/id/eprint/21163/13/book41%20The%20identification%20and%20control%20of%20a%20finger%20exoskeleton%20for%20grasping%20rehabilitation.pdf
http://umpir.ump.edu.my/id/eprint/21163/
https://doi.org/10.1007/978-981-10-8788-2_17
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Institution: Universiti Malaysia Pahang
Language: English
English
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Summary:This paper evaluates the efficacy of different classical control architectures in performing grasping motion. The exoskeleton system was obtained via system identification method in which the input and output data was measured by means of current sensor (ACS712) and encoder attached to a DC geared motor (SPG30e-270k). The data obtained is split with a ratio of 70:30 for estimation and validation, respectively. The transfer function of the system is evaluated by varying the number of poles and zeros that are able to fit well with validation data. The performance of the classical P, PI, PD and PID control techniques were then evaluated in its ability to track the desired trajectory. It was demonstrated from the study that the PID controller provides the least steady state error as well as a reasonably fast settling time.