Universiti Teknologi Malaysia Institutional Repository

Model predictive control for induction motor fed by 5-Level Cascaded H-Bridge Inverter

Abobaker, Abobaker K. and Mohamad Nordin, Norjulia and Ahmad Azli, Naziha and Ayop, Razman and Mohd. Subha, Nurul Adilla (2022) Model predictive control for induction motor fed by 5-Level Cascaded H-Bridge Inverter. In: Proceedings of the 11th International Conference on Robotics, Vision, Signal Processing and Power Applications Enhancing Research and Innovation through the Fourth Industrial Revolution. Lecture Notes in Electrical Engineering, 829 (NA). Springer Science and Business Media Deutschland GmbH, Singapore, pp. 144-149. ISBN 978-981168128-8

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Official URL: http://dx.doi.org/10.1007/978-981-16-8129-5_23

Abstract

One of the most exciting and challenging problem is the control of induction machines (IMs). An advanced control strategy with a three-phase inverter to drive an induction motor (IM) is a conventional model predictive control (MPC). However, the use of a conventional MPC 3-phase inverter leads to the generation of extensive harmonic content due to a limited voltage vector, resulting in high ripples of torque and flux. Besides, the calculation of weighting factor by error is complex and so is the selection for three different objectives. Hence, this paper aims to propose simple technique with a multilevel cascaded high bridge inverter (5-level CHB) for predictive torque and flux control to drive IM with lower harmonic content in stator current without using the weighting factor to optimize the MPC cost function. Precisely in this method, the torque is being calculated using one cost function while the flux is being calculated using a decupled cost function. It is expected to improve steady-state performance, achieves a more effective performance, and decreases torque and flux ripples in terms of current distortion.

Item Type:Book Section
Uncontrolled Keywords:induction motor, model predictive control, multilevel inverter
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Faculty of Engineering - School of Electrical
ID Code:100522
Deposited By: Yanti Mohd Shah
Deposited On:14 Apr 2023 02:45
Last Modified:14 Apr 2023 02:45

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