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Fault-Tolerant Control for Six-Phase PMSM Drive System via Intelligent Complementary Sliding-Mode Control Using TSKFNN-AMF
Abstract
An intelligent complementary sliding-mode control (CSMC) (ICSMC) is proposed in this paper for the fault-tolerant control of a six-phase permanent-magnet synchronous motor (PMSM) drive system with open phases. First, the dynamics of the six-phase PMSM drive system with a lumped uncertainty is described in detail. Then, the fault detection and operating decision method is briefly introduced. Moreover, a CSMC is designed to stabilize the fault-tolerant control of the six-phase PMSM drive system. Furthermore, to improve the required control performance and to maintain the stability of the six-phase PMSM drive system under faulty condition, the ICSMC is developed. In this approach, a Takagi-Sugeno-Kang-type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) estimator with accurate approximation capability is employed to estimate the lumped uncertainty. In addition, the adaptive learning algorithms for the online training of the TSKFNN-AMF are derived using the Lyapunov theorem to guarantee the closed-loop stability. Additionally, to enhance the control performance of the proposed intelligent fault-tolerant control, a 32-b floating-point digital signal processor, TMS320F28335, is adopted for the implementation of the proposed fault-tolerant control system. Finally, some experimental results are illustrated to demonstrate the validity of the proposed fault-tolerant control for the six-phase PMSM drive system via ICSMC.
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Control strategies for open-phase fault of multiphase motors focus on minimization of torque ripples and the principle of unchanged magnetomotive force before and after the fault.
“All these solutions were proposed for open-phase fault of the multiphase motors and were focused on the minimization of the torque ripples and the principle of unchanged magnetomotive force before and after the fault.”
From Fault Diagnosis and Fault-Tolerant Control of PMSM Drives–State of the Art and Future Challenges (2022) · cites this paper as [316]
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Metadata
- Authors
- Lin, F.-J., Hung, Y.-C., & Tsai, M.-T.
- Affiliations
- National Central University (TW)
- ORCID
- Lin, Faa-Jeng
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2013-12
- Volume
- 60
- Issue
- 12
- Pages
- 5747-5762
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W1987611823
- Cited by
- 145
- References
- 40
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 4 · 2023: 6 · 2022: 13 · 2021: 9 · 2020: 10 · 2019: 15 · 2018: 18 · 2017: 14 · 2016: 13 · 2015: 16 · 2014: 9 · 2013: 2
- FWCI
- 8.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Industrial Electronics (publishedVersion)
- Funders
- National Science Council
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Sensorless Control of Electric Motors
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Motor Design and Analysis
- Keywords
- fault-tolerant control, six-phase permanent magnet synchronous motor, lumped uncertainty estimation, adaptive learning algorithms, Lyapunov stability, open-phase fault, motor drives
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