Robust Model Predictive Control of Permanent Magnet Synchronous Motor Under Parameter Mismatch
- 1st Edition - July 30, 2026
- Latest edition
- Authors: Gongping Wu, Sheng Huang, Qiuwei Wu, Vladimir Terzija
- Language: English
Permanent magnet synchronous motors (PMSMs) are essential in electromechanical systems like urban rail vehicles and wind power generation, thanks to their fast torque response and… Read more
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Description
Description
Key features
Key features
- Provides understanding of sensitivity analysis and predictive control of permanent magnet synchronous motor with parameter mismatches, and increases opportunity to conduct research in this field by providing the model predictive control methods and code
- Offers the latest developments in the model predictive control methods of permanent magnet synchronous motors
- A technical book for engineers in the industrial motor applications
Readership
Readership
Table of contents
Table of contents
2. Research Status and Challenges of Model Predictive Control in Motor Systems
3. Modeling and Parameters Sensitivity Analysis of PMSM Under Parameter Mismatch
4. Model Predictive Control of PMSM Under Normal Conditions
5. Novel Predictive Stator Flux Control Techniques for Three-phase PMSM Considering Flux Linkage Parameter Mismatch
6. Robust Fault-Tolerant Predictive Current Control for Three-phase PMSM Considering Demagnetization Fault
7. Robust Cascaded Model-Free Tolerant Control With Parameters Mismatch Fault Diagnosis for Three-phase PMSM
8. Robust Cascaded Predictive Voltage Control for Three-phase PMSM Without Model Parameter Dependency
9. Robust Predictive Torque Control of Modular PMSM for High Power Traction Application Under Parameter Mismatch
10. Model-free Predictive Flux Vector Control for Modular PMSM Considering Parameters Mismatch
11. Predictive Torque and Stator Flux Control for Modular PMSM With Parameter Robustness Improvement
12. Robust Predictive Power Control of Modular PMSM with Inductance Parameter Mismatch
Product details
Product details
- Edition: 1
- Latest edition
- Published: July 30, 2026
- Language: English
About the authors
About the authors
GW
Gongping Wu
Gongping Wu received the Ph.D. degree in electrical engineering from the College of Electrical and Information Engineering, Hunan University, Changsha, China, in 2021. He studied with College of Electronic and Information Engineering, Tongji University, Shanghai, China, from September 2011 to September 2013. From 2019 to 2021, he was a Visiting student with the Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark. He is an Associate Professor with the College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China. His current research interests include motor fault diagnosis, model predictive control, and permanent magnet synchronous motor systems.
SH
Sheng Huang
Sheng Huang received the M.S. and Ph.D. degrees in electrical engineering from the College of Electrical and Information Engineering, Hunan University, Changsha, China, in 2012 and 2016, respectively. Since 2023, he has been a Professor with College of Electrical and Information Engineering, Hunan University. His research interests include renewable energy generation, modeling and integration study of wind power, and permanent magnet synchronous motor systems.
QW
Qiuwei Wu
Qiuwei Wu received the PhD degree in Electrical Engineering from Nanyang Technological University, Singapore, in 2009. He is a professor with the School of Electronics, Electrical Engineering, and Computer Science (EEECS), Queen’s University Belfast, the UK. His research interests are distributed optimal operation and control of low carbon power and energy systems, including distributed optimal control of wind power, optimal operation of active distribution networks, and optimal operation and planning of integrated energy systems.
VT