Fast response predictive controllers for mono-inverter dual parallel permanent magnet synchronous

Document Type : Research Article

Authors

1 Department of Electrical Engineering, Faculty of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Department of Electrical Engineering, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran.

3 Department of Electrical Engineering, College of Technical and Engineering West Tehran Branch, Islamic Azad University, Tehran, Iran.

Abstract

The method of Mono-Inverter Dual-Parallel (MIDP) motors has been noticed in the drive of multi-motor systems in order to reduce the number of power electronic devices as well as the volume, weight, and cost of the drive system. The load torque imbalance in motors has been one of the main problems of these systems because of feeding the motors by a single inverter. Some control methods have also been proposed in this field and studies are ongoing. This paper deals with an effective Model Predictive Control (MPC) method for the design of speed and current controllers in MIDP motors. Pontryagin’s Maximum Principle (PMP) and the Lagrange method are used in designing the current and speed controllers, respectively. The current controller generates control signals as linear-parametric functions through offline solving of the quadratic-linear cost function. Instead of using conventional Proportional Integral (PI) controllers in the speed control loop, speed controllers are designed based on the regulating Kinetic energy of the motors. After deriving and simplifying the mathematical equations, the proposed method is simulated. Simulation results are compared with Finite Control Set-Model Predictive Control (FCS-MPC). These results validate the prompt and accurate performance of the proposed controllers in transient and steady states.

Keywords

Main Subjects

References

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Scientia Iranica
Volume 32, Issue 10
Transactions on Computer Science & Engineering and Electrical Engineering
May and June 2026 Article ID:7185

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  • Receive Date: 02 October 2022
  • Revise Date: 30 November 2022
  • Accept Date: 05 March 2023

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