International Journal of Electrical and Computer Engineering (IJECE) Vol. 11, No. 5, October 2021, pp. 3913~3923 ISSN: 2088-8708, DOI: 10.11591/ijece.v11i5.pp3913-3923  3913 Journal homepage: http://ijece.iaescore.com Pneumatic positioning control system using constrained model predictive controller: Experimental repeatability test Siti Fatimah Sulaiman 1 , M. F. Rahmat 2 , Ahmad Athif Faudzi 3 , Khairuddin Osman 4 , S. I. Samsudin 5 , A. F. Z. Abidin 6 , Noor Asyikin Sulaiman 7 1,4,5,7 Centre for Telecommunication Research and Innovation (CeTRI), Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka, Malaysia 2,3 School of Electrical Engineering, Universiti Teknologi Malaysia, Malaysia 2,3 Centre for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, Malaysia 6 Faculty of Electrical and Electronics Engineering Technology, Universiti Teknikal Malaysia Melaka, Malaysia Article Info ABSTRACT Article history: Received Oct 16, 2020 Revised Mar 2, 2021 Accepted Mar 23, 2021 Most of the controllers that were proposed to control the pneumatic positioning system did not consider the limitations or constraints of the system in their algorithms. Non-compliance with the prescribed system constraints may damage the pneumatic components and adversely affect its positioning accuracy, especially when the system is controlled in real-time environment. Model predictive controller (MPC) is one of the predictive controllers that is able to consider the constraint of the system in its algorithm. Therefore, constrained MPC (CMPC) was proposed in this study to improve the accuracy of pneumatic positioning system while considering the constraints of the system. The mathematical model of pneumatic system was determined by system identification technique and the control signal to the valves were considered as the constraints of the pneumatic system when developing the controller. In order to verify the accuracy and reliability of CMPC, repetitive experiments on the CMPC strategy was implemented. The existing predictive controller, that was used to control the pneumatic system such as predictive functional control (PFC), was also compared. The experimental results revealed that CMPC effectively improved the position accuracy of the pneumatic system compared to PFC strategy. However, CMPC not capable to provide a fast response as PFC. Keywords: Constraint MPC Pneumatic system Position control System identification This is an open access article under the CC BY-SA license. Corresponding Author: Siti Fatimah Sulaiman Centre for Telecommunication Research and Innovation (CeTRI) Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka 76100 Durian Tunggal, Melaka, Malaysia Email: sitifatimahsulaiman@utem.edu.my 1. INTRODUCTION Essentially, modern pneumatic system incorporates pneumatic cylinder actuator, microprocessor, valves, and various microsensors in a single system; thus, making it more complicated and sophisticated compared to the conventional pneumatic system. However, the complexities of the modern pneumatic system makes the modelling and controlling, especially to acquire an accurate position control of the pneumatic system very challenging due to the issues of parameter uncertainties and nonlinearities [1]. For wider applications, the pneumatic system must have the capability to attain fast response and accurate positioning control [2].