Submission Deadline: 30 December 2025 View: 221 Submit to Special Issue
Prof. Dr. Jun Cai
Email: j.cai@nuist.edu.cn
Affiliation: School of Automation, Nanjing University of Information Science and Technology, Nanjing, 211544, China
Research Interests: Model predictive control, switched reluctance motor, permanent magnet synchronous motor (PMSM), torque ripple, AI technology, sensorless technology, electric vehicle
Dr. Ying Yan
Email: ying.yan@nuist.edu.cn
Affiliation: School of Automation, Nanjing University of Information Science and Technology, Nanjing, 211544, China
Research Interests: Fault Detection, Diagnosis, and Prognosis for Cyber Physical Systems; Machine Learning and Deep Learning; Pattern Recognition; EEG Analysis; Optimization; Production Planning, Scheduling, and Control
Model Predictive Control (MPC) has several advantages such as fast dynamic response, simultaneous pursuit of multiple control objectives, and easy inclusion of nonlinear constraints, which have attracted great attentions in modern electrical machine drive control. Recently, the MPC is also widely studied in permanent magnet synchronous motor (PMSM) and switched reluctance motor (SRM) drives. The key issues of MPC in motor drives are to ensure integration of MPC with other high performance control strategies, improve stability, and lower computational burdens.
This Special Issue aims to collect, present and disseminate the most recent advances regarding the control of electrical machine drives using MPC techniques. Topics of interest include, but are not limited to:
· Novel MPC theory and applications
· MPC control of PMSM and SRM with lowed computation burden.
· Sensorless MPC control of PMSM and SRM
· MPC control of SRM with torque ripple suppression
· MPC control of PMSM system with complex converter topology
· MPC control of PMSM and SRM with fault-tolerant capability
· MPC control of EV motor drives
· MPC control of motor drives with adaptive parameter identification
· AI technology assisted MPC control in motor drives
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