Sensorless control system for assistive robotic ankle-foot
This article presents a novel sensorless control system of assistive robotic ankle-foot prosthesis, two estimation algorithms were developed and an analogy between them has been made. The system actuator’s motor is a permanent magnet synchronous motor, unlike other powered ankle-foot, where the brus...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2018-05-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/1729881418775854 |
| _version_ | 1818314076104687616 |
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| author | Mouaz Al Kouzbary Noor Azuan Abu Osman Ahmad Khairi Abdul Wahab |
| author_facet | Mouaz Al Kouzbary Noor Azuan Abu Osman Ahmad Khairi Abdul Wahab |
| author_sort | Mouaz Al Kouzbary |
| collection | DOAJ |
| description | This article presents a novel sensorless control system of assistive robotic ankle-foot prosthesis, two estimation algorithms were developed and an analogy between them has been made. The system actuator’s motor is a permanent magnet synchronous motor, unlike other powered ankle-foot, where the brushless DC motor and DC motor were used. Utilizing the permanent magnet synchronous motor will reduce the torque ripples and increase system ability to be overloaded compared to systems which utilize the brushless DC motor. Moreover, the ability of the machine to operate in all speed range makes this machine more suitable for the application. Both estimation algorithms are built using C-code and assessed in MATLAB Simulink. The estimation algorithms are used to provide motor and powered ankle-foot’s angular speed and position. Two-level control system is used to evaluate the estimation algorithms; the control system role is to mimic biological ankle-foot performance during normal ground level walking speed. Based on the result of this article the unscented Kalman filter (UKF) is applicable for the application, as a result of the observer ability to estimate the motor load and angular position. On the other hand, extended Kalman filter (EKF) accuracy is affected by the load applied to the motor. Furthermore, the angular position is evaluated by integration of the angular speed which means integration of angular speed estimation error. |
| first_indexed | 2024-12-13T08:43:53Z |
| format | Article |
| id | doaj.art-9518dca107384523b655518eaa1708dc |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-13T08:43:53Z |
| publishDate | 2018-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-9518dca107384523b655518eaa1708dc2022-12-21T23:53:29ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142018-05-011510.1177/1729881418775854Sensorless control system for assistive robotic ankle-footMouaz Al KouzbaryNoor Azuan Abu OsmanAhmad Khairi Abdul WahabThis article presents a novel sensorless control system of assistive robotic ankle-foot prosthesis, two estimation algorithms were developed and an analogy between them has been made. The system actuator’s motor is a permanent magnet synchronous motor, unlike other powered ankle-foot, where the brushless DC motor and DC motor were used. Utilizing the permanent magnet synchronous motor will reduce the torque ripples and increase system ability to be overloaded compared to systems which utilize the brushless DC motor. Moreover, the ability of the machine to operate in all speed range makes this machine more suitable for the application. Both estimation algorithms are built using C-code and assessed in MATLAB Simulink. The estimation algorithms are used to provide motor and powered ankle-foot’s angular speed and position. Two-level control system is used to evaluate the estimation algorithms; the control system role is to mimic biological ankle-foot performance during normal ground level walking speed. Based on the result of this article the unscented Kalman filter (UKF) is applicable for the application, as a result of the observer ability to estimate the motor load and angular position. On the other hand, extended Kalman filter (EKF) accuracy is affected by the load applied to the motor. Furthermore, the angular position is evaluated by integration of the angular speed which means integration of angular speed estimation error.https://doi.org/10.1177/1729881418775854 |
| spellingShingle | Mouaz Al Kouzbary Noor Azuan Abu Osman Ahmad Khairi Abdul Wahab Sensorless control system for assistive robotic ankle-foot International Journal of Advanced Robotic Systems |
| title | Sensorless control system for assistive robotic ankle-foot |
| title_full | Sensorless control system for assistive robotic ankle-foot |
| title_fullStr | Sensorless control system for assistive robotic ankle-foot |
| title_full_unstemmed | Sensorless control system for assistive robotic ankle-foot |
| title_short | Sensorless control system for assistive robotic ankle-foot |
| title_sort | sensorless control system for assistive robotic ankle foot |
| url | https://doi.org/10.1177/1729881418775854 |
| work_keys_str_mv | AT mouazalkouzbary sensorlesscontrolsystemforassistiveroboticanklefoot AT noorazuanabuosman sensorlesscontrolsystemforassistiveroboticanklefoot AT ahmadkhairiabdulwahab sensorlesscontrolsystemforassistiveroboticanklefoot |