Fault Analysis of Electrical Machine Drives Employing Novel Model Predictive Control

Authors

  • Yogita P. Akhare Prairie View A& M University, U.S.A
  • Warsame H. Ali Prairie View A&M University, U.S.A
  • John H. Fuller Prairie View A&M University, U.S.A
  • John O. Attia Prairie View A&M University, U.S.A

DOI:

https://doi.org/10.31695/IJASRE.2020.33909

Keywords:

Novel Model Predictive Control , MPC, Synchronous Servo Motor Drive , Insulated-Gate Bipolar Transistor

Abstract

Electrical machine drives play a crucial role in various industrial applications. Therefore, its control system design became more significant in the last decades. Numerous high powers and high-efficiency machine drives require faultless continuous operation. Fault-tolerant control is a productive solution for the improvement of the reliability of the machine drives. Model Predictive Control (MPC) is an optimal control algorithm developed for constrained control of Multi-Input-Multi-Output (MIMO) systems. MPC can handle MIMO systems and can incorporate several constraints in the form of equalities and inequalities. A Novel Model Predictive Control(NMPC) method for a Synchronous Servo Motor Drive (SSMD) integrating a real-time fault diagnostic method for Insulated Gate Bipolar Transistor ((IGBT) faults in an inverter has been presented in this paper. NMPC ensures the system's better performance and minimal fault clearance time. 

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Yogita P. Akhare, Warsame H. Ali, John H. Fuller, & John O. Attia. (2020). Fault Analysis of Electrical Machine Drives Employing Novel Model Predictive Control . International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE, 6(10), 79–90. https://doi.org/10.31695/IJASRE.2020.33909

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