Title: A new reference model-based fixed-structure controller for industrial applications
Authors: Muhammad Zakwan; Muhammad Hamza Hashmi; Mukhtar Ali; Shakil Ahmed
Addresses: Center for Excellence in Sciences and Applied Technology (CESAT), Plot 94, Sector H-11/4, Islamabad, Pakistan ' Center for Excellence in Sciences and Applied Technology (CESAT), Plot 94, Sector H-11/4, Islamabad, Pakistan ' Center for Excellence in Sciences and Applied Technology (CESAT), Plot 94, Sector H-11/4, Islamabad, Pakistan ' Center for Excellence in Sciences and Applied Technology (CESAT), Plot 94, Sector H-11/4, Islamabad, Pakistan
Abstract: This paper introduces a new approach to design a fixed-structure controller for those industrial applications, where mathematical model of the plant is not known. The design methodology is composed of two steps. First, black-box system identification is used to obtain a mathematical model of plant and second, a fixed-structure controller is designed based on reference model defined by closed-loop performance. For controller identification, prediction error method (PEM) is considered, which uses the off-line generated input-output inherently noise free data using the reference model. Due to fixed design structure, the controller is independent of plant's order. The proposed approach is tested on a lab-based real-time magnetic levitation system (MLS). The results show effectiveness of the proposed approach with good reference tracking and robustness properties. The proposed approach emerged a lower order controller which is computationally efficient and easy to implement. Compare to other data-driven techniques, inverse mapping of the reference model is not required and the performance versus design/tuning time comparison with conventional proportional integral derivative (PID) controller is also improved.
Keywords: system identification; reference model; fixed-structure controller; magnetic levitation system; MLS.
International Journal of Automation and Logistics, 2021 Vol.3 No.2, pp.89 - 103
Received: 18 Mar 2017
Accepted: 21 Sep 2017
Published online: 02 Feb 2021 *