Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation
The issues of inaccurate positioning control have made an industrial use of pneumatic actuator remains restricted to certain applications only. Non-compliance with system limits and properly control the operating system may also degrade the performance of pneumatic positioning systems. This study pr...
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2021
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my.utm.955432022-05-31T12:46:12Z http://eprints.utm.my/id/eprint/95543/ Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation Sulaiman, S. F. Rahmat, M. F. Faudzi, A. A. Osman, K. Sunar, N. H. TK Electrical engineering. Electronics Nuclear engineering The issues of inaccurate positioning control have made an industrial use of pneumatic actuator remains restricted to certain applications only. Non-compliance with system limits and properly control the operating system may also degrade the performance of pneumatic positioning systems. This study proposed a new approach to enhance pneumatic positioning system while considering the constraints of system. Firstly, a mathematical model that represented the pneumatic system was determined by system identification approach. Secondly, model predictive controller (MPC) was developed as a primary controller to control the pneumatic positioning system, which took into account the constraints of the system. Next, to enhance the performance of the overall system, nonlinear gain function was incorporated within the MPC algorithm. Finally, the performances were compared with other control methods such as constrained MPC (CMPC), proportional-integral (PI), and predictive functional control with observer (PFC-O). The validation based on real-time experimental results for 100 mm positioning control revealed that the incorporation of nonlinear gain within the MPC algorithm improved 21.03% and 2.69% of the speed response given by CMPC and PFC-O, and reduced 100% of the overshoot given by CMPC and PI controller; thus, providing fast and accurate pneumatic positioning control system. Institute of Advanced Engineering and Science 2021 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/95543/1/MFRahmat2021_EnhancementinPneumaticPositioningSystem.pdf Sulaiman, S. F. and Rahmat, M. F. and Faudzi, A. A. and Osman, K. and Sunar, N. H. (2021) Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation. Indonesian Journal of Electrical Engineering and Computer Science, 23 (3). 1385 -1397. ISSN 2502-4752 http://dx.doi.org/10.11591/ijeecs.v23.i3.pp1385-1397 DOI: 10.11591/ijeecs.v23.i3.pp1385-1397 |
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TK Electrical engineering. Electronics Nuclear engineering Sulaiman, S. F. Rahmat, M. F. Faudzi, A. A. Osman, K. Sunar, N. H. Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
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The issues of inaccurate positioning control have made an industrial use of pneumatic actuator remains restricted to certain applications only. Non-compliance with system limits and properly control the operating system may also degrade the performance of pneumatic positioning systems. This study proposed a new approach to enhance pneumatic positioning system while considering the constraints of system. Firstly, a mathematical model that represented the pneumatic system was determined by system identification approach. Secondly, model predictive controller (MPC) was developed as a primary controller to control the pneumatic positioning system, which took into account the constraints of the system. Next, to enhance the performance of the overall system, nonlinear gain function was incorporated within the MPC algorithm. Finally, the performances were compared with other control methods such as constrained MPC (CMPC), proportional-integral (PI), and predictive functional control with observer (PFC-O). The validation based on real-time experimental results for 100 mm positioning control revealed that the incorporation of nonlinear gain within the MPC algorithm improved 21.03% and 2.69% of the speed response given by CMPC and PFC-O, and reduced 100% of the overshoot given by CMPC and PI controller; thus, providing fast and accurate pneumatic positioning control system. |
format |
Article |
author |
Sulaiman, S. F. Rahmat, M. F. Faudzi, A. A. Osman, K. Sunar, N. H. |
author_facet |
Sulaiman, S. F. Rahmat, M. F. Faudzi, A. A. Osman, K. Sunar, N. H. |
author_sort |
Sulaiman, S. F. |
title |
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
title_short |
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
title_full |
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
title_fullStr |
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
title_full_unstemmed |
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
title_sort |
enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation |
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Institute of Advanced Engineering and Science |
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2021 |
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http://eprints.utm.my/id/eprint/95543/1/MFRahmat2021_EnhancementinPneumaticPositioningSystem.pdf http://eprints.utm.my/id/eprint/95543/ http://dx.doi.org/10.11591/ijeecs.v23.i3.pp1385-1397 |
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13.18916 |