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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Main Authors: Sulaiman, Siti Fatimah (Author), Rahmat, M. F. (Author), Faudzi, Ahmad Athif (Author), Osman, Khairuddin (Author), Sunar, N. H. (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2021-09-01.
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042 |a dc 
100 1 0 |a Sulaiman, Siti Fatimah  |e author 
100 1 0 |e contributor 
700 1 0 |a Rahmat, M. F.  |e author 
700 1 0 |a Faudzi, Ahmad Athif  |e author 
700 1 0 |a Osman, Khairuddin  |e author 
700 1 0 |a Sunar, N. H.  |e author 
245 0 0 |a Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation 
260 |b Institute of Advanced Engineering and Science,   |c 2021-09-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25667 
520 |a 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. 
540 |a Copyright (c) 2021 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690
690 |a Pneumatic actuator; Position control; Predictive control; System identification; Transient response; 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 23, No 3: September 2021; 1385-1397 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v23.i3 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25667/15377 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25667/15377  |z Get fulltext