Model Predictive Control and Fault Diagnosis for Multiphase Electric Drives

Dear Colleagues,

This Special Issue aims to showcase the latest advancements and research in the field of model predictive control (MPC) and fault diagnosis for multiphase electric drives. Unlike their three-phase counterparts, multiphase electric drives exhibit exceptional fault-tolerant capabilities, which make them the perfect candidate for aerospace, traction, and wind energy, where reliability is a key requirement. Even though multiphase electric drives offer the possibility to operate in post-fault conditions, the rapid and accurate detection of faults is still of extreme importance for promptly reconfiguring the control strategy according to the new operating conditions. Hence, the development of effective control strategies and fault diagnosis techniques is crucial for ensuring the reliable and efficient operation of multiphase electric drives.

The objective of this Special Issue is to provide a platform for researchers and industry experts to share their innovative approaches, methodologies, and practical implementations in the areas of MPC and fault diagnosis for multiphase electric drives. It will serve as a comprehensive resource for both academia and industry professionals seeking to enhance the performance, efficiency, reliability, and safety of multiphase electric drive systems.

Researchers and practitioners are invited to contribute their original research articles, case studies, and reviews that address the challenges and advancements in model predictive control and fault diagnosis for multiphase electric drives. All submissions will undergo a rigorous peer-review process to ensure the high quality and relevance of the published content.

Topics of interest include, but are not limited to:

1. Novel MPC algorithms for multiphase electric drives;
2. Advanced fault diagnosis and detection techniques;
3. Real-time implementation of MPC for multiphase electric drives;
4. Condition monitoring and prognosis methods;
5. Applications of machine learning and artificial intelligence in MPC and fault diagnosis;
6. Optimization methods to enhance the performance of multiphase electric drive systems;
7. Case studies and practical applications in various industrial sectors.

Dr. Pedro Gonçalves
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• model predictive control (MPC)
• fault diagnosis
• fault tolerance
• multiphase electric drives
• multiphase machines