Robust Cascaded Model-Free Tolerant Control With Parameters Mismatch Fault Diagnosis for PMSM Drive System
Since the parameters mismatch fault caused by the mismatch between motor parameters and model predictive controller parameters can seriously affect the performance of the drive system, it is necessary to investigate parameters mismatch fault diagnosis and tolerant control. In this study, a novel robust cascaded model-free tolerant control (RCM-FTC) method with parameters mismatch fault diagnosis is proposed for a permanent magnet synchronous motor (PMSM) drive system, which can effectively improve the control performance of stator flux and torque under parameters mismatch faults. The parameters mismatch fault sensitivity of the PMSM drive system is analyzed, and a novel ultralocal model is established under the parameters mismatch fault. The multivariable integral terminal sliding mode observer (MIT-SMO) with improved sliding mode reaching law is designed to diagnose parameters mismatch faults and identify operating states in the PMSM drive system. The robust cascaded speed loop and stator flux loop control strategy are proposed for parameters mismatch faults by utilizing the model-free sliding mode control algorithm, which can eliminate the impact of parameters mismatch faults on the PMSM drive system. The test results demonstrate the effectiveness of the proposed RCM-FTC method in significantly eliminating stator flux/torque ripple and improving fault tolerance capabilities in the case of parameters mismatch faults.
Authors
- Jing He (ORCID: https://orcid.org/0000-0002-3650-3270)
- Zhuo Long (ORCID: https://orcid.org/0000-0001-5018-7086)
- Gongping Wu (ORCID: https://orcid.org/0000-0002-8855-781X)
- Xiao Hu (ORCID: https://orcid.org/0000-0002-5971-701X)
- Zewen Li (ORCID: https://orcid.org/0000-0002-5734-4002)
Institutions
- Hunan University of Technology (CN)
- Changsha University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-11-15
- DOI
- https://doi.org/10.1109/jsen.2024.3495019
- Citations
- 5
- Primary Topic
- Fault Detection and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.64
Funders
- National Natural Science Foundation of China