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Article

Modeling and Fuzzy FOPID Controller Tuned by PSO for Pneumatic Positioning System

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Department of Control and Mechatronics Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
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Department of Control Engineering, College of Electronics Technology, Bani Walid P.O. Box 38645, Libya
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Centre for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia
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Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Mojtaba Ahmadieh Khanesar
Energies 2022, 15(10), 3757; https://doi.org/10.3390/en15103757
Received: 20 April 2022 / Revised: 13 May 2022 / Accepted: 18 May 2022 / Published: 19 May 2022
(This article belongs to the Section F: Electrical Engineering)
A pneumatic cylinder system is believed to be extremely nonlinear and sensitive to nonlinearities, which makes it challenging to establish precise position control of the actuator. The current research is aimed at reducing the overshoot in the response of a double-acting pneumatic actuator, namely, the IPA positioning system’s reaction time. The pneumatic system was modeled using an autoregressive with exogenous input (ARX) model structure, and the control strategy was implemented using a fuzzy fractional order proportional integral derivative (fuzzy FOPID) employing the particle swarm optimization (PSO) algorithm. This approach was used to determine the optimal controller parameters. A comparison study has been conducted to prove the advantages of utilizing a PSO fuzzy FOPID controller over PSO fuzzy PID. The controller tuning algorithm was validated and tested using a pneumatic actuator system in both simulation and real environments. From the standpoint of time-domain performance metrics, such as rising time (tr), settling time (ts), and overshoot (OS%), the PSO fuzzy FOPID controller outperforms the PSO Fuzzy PID controller in terms of dynamic performance. View Full-Text
Keywords: intelligent pneumatic actuators; fuzzy FOPID; fuzzy PID; PSO algorithm intelligent pneumatic actuators; fuzzy FOPID; fuzzy PID; PSO algorithm
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MDPI and ACS Style

Muftah, M.N.; Faudzi, A.A.M.; Sahlan, S.; Shouran, M. Modeling and Fuzzy FOPID Controller Tuned by PSO for Pneumatic Positioning System. Energies 2022, 15, 3757. https://doi.org/10.3390/en15103757

AMA Style

Muftah MN, Faudzi AAM, Sahlan S, Shouran M. Modeling and Fuzzy FOPID Controller Tuned by PSO for Pneumatic Positioning System. Energies. 2022; 15(10):3757. https://doi.org/10.3390/en15103757

Chicago/Turabian Style

Muftah, Mohamed Naji, Ahmad Athif Mohd Faudzi, Shafishuhaza Sahlan, and Mokhtar Shouran. 2022. "Modeling and Fuzzy FOPID Controller Tuned by PSO for Pneumatic Positioning System" Energies 15, no. 10: 3757. https://doi.org/10.3390/en15103757

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