Journal article
Global position tracking control of PMSM servo system via internal model approach and experimental validations
International Journal of Robust and Nonlinear Control, Vol.32(16), pp.9017-9033
2022
Abstract
In practical engineering, load torque disturbance and parameter uncertainties are two important factors, which may deteriorate the tracking accuracy of permanent magnet synchronous motor (PMSM) servo system. Therefore, its global position tracking control problem is a challenging task when the load torque disturbance is time-varying and the motor parameters are unknown. In this article, an internal model controller based on global robust output regulation (GROR) theory is proposed to achieve this control objective. In particular, we first formulate the global position tracking control problem as a GROR problem. Then, the GROR problem is converted into a global robust stabilization problem of an augmented system by constructing an appropriate internal model. Finally, we can stabilize the augmented system by a global stabilization controller instead of local stabilization controller used in the recent work, which guarantees global position tracking and disturbance rejection of PMSM servo system. The excellent position tracking performance of our design is demonstrated by both simulation and experimental results.
Details
- Title
- Global position tracking control of PMSM servo system via internal model approach and experimental validations
- Authors/Creators
- Z. Ping (Author/Creator) - Hefei University of TechnologyY. Jia (Author/Creator) - Hefei University of TechnologyY. Li (Author/Creator) - China Aerospace Science and Industry Corporation (China)Y. Huang (Author/Creator) - Hefei University of TechnologyH. Wang (Author/Creator) - Murdoch UniversityJ‐G Lu (Author/Creator)
- Publication Details
- International Journal of Robust and Nonlinear Control, Vol.32(16), pp.9017-9033
- Publisher
- John Wiley & Sons, Ltd.
- Identifiers
- 991005542354007891
- Copyright
- © 2022 John Wiley & Sons Ltd.
- Murdoch Affiliation
- College of Science, Health, Engineering and Education
- Language
- English
- Resource Type
- Journal article
Metrics
40 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Industry collaboration
- Domestic collaboration
- International collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.136 Electric Motor Control
- Web Of Science research areas
- Automation & Control Systems
- Engineering, Electrical & Electronic
- Mathematics, Applied
- ESI research areas
- Engineering