Model Predictive Control: Future Trends and Advances in Motors
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 May 2024 | Viewed by 454
Special Issue Editors
Interests: digital control of power electronics converters; fault diagnosis; fault-tolerant control of ac motor drives and wind turbine systems
Interests: diagnosis and fault tolerance of electrical machines, power electronics and drives
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The model predictive control (MPC) of electrical drives has gained impressive attention. It has distinguished itself from classical vector and direct control techniques due to its ability to deal straightforwardly and intuitively with multi-objective control and integrate nonlinearities and constraints into a predefined cost function while providing a fast dynamic response and superior performance. Although advantageous, the lifetime performance of this modern control can be limited. As in any model-based control, the closed-loop performance highly depends on how accurately the electrical drive is modeled. On the other hand, the MPC computation burdens reduction, the weighting factor tuning as well as the switching frequency control, are topics of interest that require further investigation.
This Special Issue aims to bring together leading academic scientists, researchers and practicing engineers to exchange and share their experiences and research results in the aforementioned fields, indicating the future trends for the model predictive control of electrical drives.
Topics include, but are not limited to, the following research areas:
- Latest developments and improvements of predictive control algorithms;
- MPC for electrical drives applications: three-phase and multiphase induction motors, PMSMs, SynRMs, etc.;
- Model-free predictive control solutions;
- Complexity and computation burdens reduction;
- Switching frequency and weighting factor control;
- Artificial intelligence and machine learning in MPC.
Dr. Imed Jlassi
Prof. Dr. Antonio J. Marques Cardoso
Guest Editors
Manuscript Submission Information
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Keywords
- model predictive control
- electrical motors
- electrical drives applications
- control performance
