Masters Theses
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 bibliographical references.
Rights
© 2015 Xin Li, All rights reserved.
Document Type
Thesis - Open Access
File Type
text
Language
English
Subject Headings
Reluctance motorsElectric currents -- MeasurementElectric current converters -- Mathematical modelsInductance
Thesis Number
T 10682
Electronic OCLC #
913486564
Recommended Citation
Li, Xin, "Model predictive current control of switched reluctance motor with inductance auto-calibration" (2015). Masters Theses. 7404.
https://scholarsmine.mst.edu/masters_theses/7404