Suboptimal Control Scheme Design for Interior Permanent-Magnet Synchronous Motors: An SDRE-Based Approach
- Authors
- Ton Duc Do; Kwak, Sangshin; Choi, Han Ho; Jung, Jin-Woo
- Issue Date
- Jun-2014
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Interior permanent-magnet synchronous motor (IPMSM); maximum torque per ampere (MTPA); nonlinear control; nonlinear observer; state-dependent Riccati equation (SDRE); suboptimal control; Taylor series method
- Citation
- IEEE TRANSACTIONS ON POWER ELECTRONICS, v.29, no.6, pp 3020 - 3031
- Pages
- 12
- Indexed
- SCI
SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON POWER ELECTRONICS
- Volume
- 29
- Number
- 6
- Start Page
- 3020
- End Page
- 3031
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/19528
- DOI
- 10.1109/TPEL.2013.2272582
- ISSN
- 0885-8993
1941-0107
- Abstract
- This paper designs a suboptimal speed controller as well as a suboptimal load torque observer based on state-dependent Riccati equation (SDRE) approach for interior permanent-magnet synchronous motor (IPMSM) servo systems. First, dynamic equations of the IPMSMs are transformed to a suitable form that makes an SDRE-based control technique applicable. Moreover, the maximum torque per ampere (MTPA) control is incorporated to improve the torque generation in the constant torque region. The asymptotic stabilities of the proposed controller and load torque observer are fully guaranteed through an extended linear quadratic regulator (LQR) theory. This proposed method is simple to implement because the SDRE solutions are approximated off-line. The proposed observer-based suboptimal control scheme can ensure faster dynamic response, smaller steady-state error, and more robust response than the LQR and proportional-integral (PI) controller under the system parameter variations and load torque disturbances. The effectiveness of the proposed control strategy is verified via experiment.
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Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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