Date of Award

5-2021

Document Type

Dissertation - Campus Access Only

Degree Name

Doctor of Philosophy (PhD)

Degree Discipline

Electrical Engineering

Abstract

Electrical machine drives play a vital role in various industrial applications. Hence, its control system design became more significant in the last decades. In various high power and high-efficiency machine drives, continuous operation necessitates despite the fault. Fault-tolerant control is an effective solution to enhance the reliability of the machine drives. Concurrently, 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, which can incorporate several constraints in the form of equalities and inequalities. In this dissertation, a Novel Model Predictive Control (NMPC) for a machine drive considering a real-time fault diagnostic method for Insulated Gate Bipolar Transistor ((IGBT) faults in an inverter has been presented. The proposed NMPC method can also reduce the stator current’s steady errors and enhance the robustness of current control loops effectively under parameter mismatch and permanent magnet demagnetization.

Solutions exist that address motor and motor drive systems’ faults, such as singlephase, three-phase, and permanent magnet demagnetization faults. These solutions, however, are not satisfactory. For example, they do not address the control overshoot and fast-tracking of the drive system.

In this dissertation, a novel model predictive control (NMPC) method is the solution that assures the system’s better performance. Since there is no existing research that describes the common MPC for all the different types of faults in PMSM drives, a novel model predictive controller (NMPC) is designed for a permanent magnet synchronous motor (PMSM) drive considering single-phase fault, three-phase fault, and demagnetization fault. First, the mathematical modeling of the PMSM drive for the prefault and post-fault operation has been introduced, followed by the advancement of the NMPC employing to predict the current in a discrete-time calculation. The phase current can be estimated at the next sampling step to compensate for the current errors, with the modification of three-phase currents of the motor. Concurrently, the machine’s fault diagnosis carried out for the pre-fault and post-fault conditions using MATLAB/Simulink. Ultimately, the machine’s speed responses using traditional control methods compared with the NMPC under different speed references for different fault conditions. The proposed algorithm has been implemented using the Lucas Nulle Servo Drive system with MATLAB/Simulink. The complete analysis, simulation, and experimental results illustrate that the adoption of NMPC improves the speed-tracking performance and provides minimal fault clearance time compared to the existing controllers.

Committee Chair/Advisor

Warsame H. Ali

Committee Member

John O. Attia

Committee Member

John H. Fuller

Committee Member

Annamalai Annamalai

Rights

© 2021 Prairie View A & M University

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Date of Digitization

11/13/2024

Contributing Institution

John B Coleman Library

City of Publication

Prairie View

MIME Type

Application/PDF

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