Online Parameter Estimation Technique for Adaptive Control Applications of Interior PM Synchronous Motor Drives
- Authors
- Dong Quang Dang; Rafaq, Muhammad Saad; Choi, Han Ho; Jung, Jin-Woo
- Issue Date
- Mar-2016
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Adaptive decoupling proportional-integral (PI) control; affine projection algorithm; interior permanent-magnet synchronous motor (IPMSM); online parameter estimation
- Citation
- IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, v.63, no.3, pp 1438 - 1449
- Pages
- 12
- Indexed
- SCI
SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Volume
- 63
- Number
- 3
- Start Page
- 1438
- End Page
- 1449
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/19526
- DOI
- 10.1109/TIE.2015.2494534
- ISSN
- 0278-0046
1557-9948
- Abstract
- This paper proposes an online parameter estimation method based on a discrete-time dynamic model for the interior permanent-magnet synchronous motors (IPMSMs). The proposed estimation technique, which takes advantage of the difference in dynamics of motor parameters, consists of two affine projection algorithms. The first one is designed to accurately estimate the stator inductances, whereas the second one is designed to precisely estimate the stator resistance, rotor flux linkage, and load torque. In this paper, the adaptive decoupling proportional-integral (PI) controllers with the maximum torque per ampere operation, which utilize the previously identified parameters in real time, are chosen to verify the effectiveness of the proposed parameter estimation scheme. The simulation results via MATLAB/Simulink and the experimental results via a prototype IPMSM drive system with a TI TMS320F28335 DSP are presented under various conditions. A comparative study with the conventional decoupling PI control method is carried out to demonstrate the better performances (i.e., faster dynamic response, less steady-state error, more robustness, etc.) of the adaptive decoupling PI control scheme based on the proposed online parameter estimation technique.
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Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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