Special Issue "Machines Predictive Control"
Deadline for manuscript submissions: 30 April 2021.
Interests: diagnosis and fault tolerance of electrical machines, power electronics, and drives
Special Issues and Collections in MDPI journals
Special Issue in Machines: Thermal Analysis of Electric Machine Drives
Interests: digital control of power electronics converters, fault diagnosis, and fault-tolerant control of ac motor drives and wind turbine systems
In recent years, Model Predictive Control (MPC) has been a powerful advanced control technology in industrial machine drives, due to its superior control performance, excellent dynamic response and the ability to easily include multiple-objective control into the cost function. At each sampling time, MPC defines the control action by minimizing a cost function that describes the desired machine behavior. This cost function compares the predicted variables to be controlled with their references. The predicted variables are calculated from the machine model and duplicated according to the possible voltage vectors of the power converter.
In classical MPC, much attention has been paid to the control performance, through the development of several control techniques for the different power converters topologies and machines. However, there are still some issues that constitute an open topic for research. Despite the huge progress of MPC for electrical machines, the control stability and robustness under harsh operating conditions, as well as the formal way of selecting optimally the weighting factor in the cost function considering the multi-objective control, are topics of interest that require further investigation. Nowadays, with the increasing complexity of power converters and machines, the independence from the model and parameters that may change with the operating point and environment, as well as the reduction of the excessive computational burden due to the duplicated prediction have a significant impact on the machine performance and drive cost.
The aim of this Special Issue is to provide an opportunity for scientists, researchers, and practicing engineers to share and disseminate their latest discoveries and results in the aforementioned fields, indicating the future trends for machines predictive control.
Topics include, but are not limited to, the following research areas:
- New MPC of electrical machines
- Stability and robustness of MPC
- Model-free predictive control approaches
- MPC algorithms with reduced computational complexity
- Implementation issues of MPC
- Artificial intelligence and data-driven in predictive control
Prof. Dr. Antonio J. Marques Cardoso
Dr. Imed Jlassi
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 papers will be 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 1600 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.