A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles
This paper suggests a new control design based on the concept of Synergetic Control theory for controlling a one-link robot arm actuated by Pneumatic artificial muscles (PAMs) in opposing bicep/tricep positions. The synergetic control design is first established based on known system parameters. How...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/22/7/723 |
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| author | Amjad J. Humaidi Ibraheem Kasim Ibraheem Ahmad Taher Azar Musaab E. Sadiq |
| author_facet | Amjad J. Humaidi Ibraheem Kasim Ibraheem Ahmad Taher Azar Musaab E. Sadiq |
| author_sort | Amjad J. Humaidi |
| collection | DOAJ |
| description | This paper suggests a new control design based on the concept of Synergetic Control theory for controlling a one-link robot arm actuated by Pneumatic artificial muscles (PAMs) in opposing bicep/tricep positions. The synergetic control design is first established based on known system parameters. However, in real PAM-actuated systems, the uncertainties are inherited features in their parameters and hence an adaptive synergetic control algorithm is proposed and synthesized for a PAM-actuated robot arm subjected to perturbation in its parameters. The adaptive synergetic laws are developed to estimate the uncertainties and to guarantee the asymptotic stability of the adaptive synergetic controlled PAM-actuated system. The work has also presented an improvement in the performance of proposed synergetic controllers (classical and adaptive) by applying a modern optimization technique based on Particle Swarm Optimization (PSO) to tune their design parameters towards optimal dynamic performance. The effectiveness of the proposed classical and adaptive synergetic controllers has been verified via computer simulation and it has been shown that the adaptive controller could cope with uncertainties and keep the controlled system stable. The proposed optimal Adaptive Synergetic Controller (ASC) has been validated with a previous adaptive controller with the same robot structure and actuation, and it has been shown that the optimal ASC outperforms its opponent in terms of tracking speed and error. |
| first_indexed | 2024-03-10T18:46:26Z |
| format | Article |
| id | doaj.art-6467b71f85ec4345942dcdb8114535dc |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T18:46:26Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-6467b71f85ec4345942dcdb8114535dc2023-11-20T05:27:58ZengMDPI AGEntropy1099-43002020-06-0122772310.3390/e22070723A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic MusclesAmjad J. Humaidi0Ibraheem Kasim Ibraheem1Ahmad Taher Azar2Musaab E. Sadiq3Control and Systems Engineering Department, University of Technology, Baghdad 10001, IraqDepartment of Electrical Engineering, College of Engineering, University of Baghdad, Baghdad 10001, IraqRobotics and Internet-of-Things Lab (RIOTU), Prince Sultan University, Riyadh 11586, Saudi ArabiaMinistry of Trade, General Company for Grain Processing, Baghdad 10001, IraqThis paper suggests a new control design based on the concept of Synergetic Control theory for controlling a one-link robot arm actuated by Pneumatic artificial muscles (PAMs) in opposing bicep/tricep positions. The synergetic control design is first established based on known system parameters. However, in real PAM-actuated systems, the uncertainties are inherited features in their parameters and hence an adaptive synergetic control algorithm is proposed and synthesized for a PAM-actuated robot arm subjected to perturbation in its parameters. The adaptive synergetic laws are developed to estimate the uncertainties and to guarantee the asymptotic stability of the adaptive synergetic controlled PAM-actuated system. The work has also presented an improvement in the performance of proposed synergetic controllers (classical and adaptive) by applying a modern optimization technique based on Particle Swarm Optimization (PSO) to tune their design parameters towards optimal dynamic performance. The effectiveness of the proposed classical and adaptive synergetic controllers has been verified via computer simulation and it has been shown that the adaptive controller could cope with uncertainties and keep the controlled system stable. The proposed optimal Adaptive Synergetic Controller (ASC) has been validated with a previous adaptive controller with the same robot structure and actuation, and it has been shown that the optimal ASC outperforms its opponent in terms of tracking speed and error.https://www.mdpi.com/1099-4300/22/7/723Pneumatic Artificial Musclessynergetic controladaptive controlparticle swarming optimizationsingle-link robot arm |
| spellingShingle | Amjad J. Humaidi Ibraheem Kasim Ibraheem Ahmad Taher Azar Musaab E. Sadiq A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles Entropy Pneumatic Artificial Muscles synergetic control adaptive control particle swarming optimization single-link robot arm |
| title | A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles |
| title_full | A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles |
| title_fullStr | A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles |
| title_full_unstemmed | A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles |
| title_short | A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles |
| title_sort | new adaptive synergetic control design for single link robot arm actuated by pneumatic muscles |
| topic | Pneumatic Artificial Muscles synergetic control adaptive control particle swarming optimization single-link robot arm |
| url | https://www.mdpi.com/1099-4300/22/7/723 |
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