Masters Theses

Author

Xin Li

Keywords and Phrases

Current control; Motor drive

Abstract

"The thesis is composed of three papers, which investigate the application of Model Predictive Controller (MPC) for current control of Switched Reluctance Motor (SRM). Since the conventional hysteresis current control method is not suitable for high power SRM drive system with low inductance and limited switching frequency, MPC is a promising alternative approach for this application. The proposed MPC can cope with the measurement noise as well as uncertainties within the machine inductance profile. In the first paper, a MPC current control method for Double-Stator Switched Reluctance Motor (DSSRM) drives is presented. A direct adaptive estimator is incorporated to follow the inductance variations in a DSSRM. In the second paper, the Linear Quadratic (LQ) form and dynamic programming recursion for MPC are analyzed, afterwards the unconstrained MPC solution for stochastic SRM model is derived. The Kalman filter is employed to reduce the variance of measurement noises. Based on Recursive Linear-Square (RLS) estimation, the inductance profile is calibrated dynamically. In the third paper, a simplified recursive MPC current control algorithm for SRM is applied for embedded implementation. A novel auto-calibration method for inductance surface estimation is developed to improve current control performance of SRM drive in statistic terms."--Abstract, page iv.

Advisor(s)

Shamsi, Pourya

Committee Member(s)

Ferdowsi, Mehdi
Kimball, Jonathan W.

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2015

Journal article titles appearing in thesis/dissertation

  • Adaptive model predictive control for DSSRM drives
  • Model predictive current control of switched reluctance motors with inductance auto-calibration
  • Inductance surface learning for model predictive current control of switched reluctance motors

Pagination

x, 65 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2015 Xin Li, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Reluctance motors
Electric currents -- Measurement
Electric current converters -- Mathematical models
Inductance

Thesis Number

T 10682

Electronic OCLC #

913486564

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