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Simulation of Model Predictive Control MPC for Practical Design and Application

Emian Mohammad Abed Zaid Aljbory, Dr. Mahi FIrouzi, Ahmed Selman Altuma and Dr. Babak Mozafari
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Emian Mohammad Abed Zaid Aljbory: Department of Electrical and Electronic Engineering, University of Karbala, Islamic Azad University
Dr. Mahi FIrouzi: Department of Electrical and Electronic Engineering, University of Karbala, Islamic Azad University
Ahmed Selman Altuma: Department of Electrical and Electronic Engineering, University of Karbala, Islamic Azad University
Dr. Babak Mozafari: Department of Electrical and Electronic Engineering, University of Karbala, Islamic Azad University

International Journal of Research and Scientific Innovation, 2022, vol. 9, issue 11, 65-74

Abstract: The precise location control of DC servo motor is a significant issue in industry. Here examination introduce location seeking with expectation of DC motor utilizing various controls methodology. Controlling procedures is expected to reduce and minimize the consistent state errors. Utilization of model predictive controller MPC strategy also carry out such requirements. Three types of control procedures are introduced in this work. The dynamic set strategy ASM, the inside mark technique IPM, and the quick online slope technique FGM have been utilized as control techniques. Such exploration recognizes and portrays the plan decisions connected with a three kinds of control units with predictive controller for a DC servo motor. Implementation of such controllers has been confirmed along reenactment using simulation program with MATLAB software. According to the reenactment results the Comparisons among ASM, IPM, FGM and MPC controllers are inclined in this undertaking. The adjusting strategy was further effective in an enhancing the progression reaction qualities, for example, reducing the ascent time, settling time and greatest overshoot in Position control of DC servo motor. Model predictive controller strategy provides the favorite exhibition and prevalence of MPC strategy view at along alternative controlling units.

Date: 2022
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