Open AccessPneumatic positioning control system using constrained model predictive controller: Experimental repeatability test
Author(s) -
Siti Zubaidah Sulaiman,
M. F. Rahmat,
Ahmad Athif Mohd Faudzi,
Khairuddin Osman,
Sharatul Izah Samsudin,
Amar Faiz Zainal Abidin,
Noor Asyikin Sulaiman
Publication year - 2021
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v11i5.pp3913-3923
Subject(s) - model predictive control , control theory (sociology) , controller (irrigation) , computer science , reliability (semiconductor) , pneumatic actuator , repeatability , control system , control engineering , engineering , control (management) , actuator , artificial intelligence , mathematics , electrical engineering , statistics , power (physics) , physics , quantum mechanics , agronomy , biology
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.