Welcome to Model Predictive Control of Power Electronic Converters
Description: Model Predictive Control (MPC) is a conceptually simple yet powerful methodology to control power converters and electric drives. It has many advantages over traditional linear controllers including (i) faster response, (ii) high robustness to parameter variation (iii) explicit multivariable control accounting for the process and actuator constraints. The advances in processing power of digital signal processors have recently promoted MPC into the first commercial applications, which opened a door towards improved performance and efficiency of power electronic converters and drives demanded by the evolving industry applications. This course aims to provide the fundamentals required to understand, design and implement MPC to power electronic converters used for a variety of applications including grid-connected converters, drives and microgrids. The motivation is to facilitate wider and faster exploitation of MPC by bridging the gap between theory and successful industrial implementation through cooperation and exchange of experience between academic/research and industrial communities. It is envisioned for both PhD students and practicing engineers.
Some of the course contents are based on recently obtained research results. The main topics are as follows:
Introduction to Model Predictive Control (MPC) for Power Electronic Systems and Drives
Power Converter Modelling Fundamentals and Discretization
Finite-Control-Set Model Predictive Control (FCS-MPC) Principle
Periodic and Dead-Beat Control Principles
Quantitative Performance Evaluation of the FCS-MPC
Application Example: FCS-MPC in 2-level, 3 phase Voltage Source Converter for AC microgrids
Laboratory Exercises (Simulation + Laboratory Demonstration
Prerequisites: General knowledge in electrical AC circuits and electrical power engineering, preferably background at the graduate level in power electronics.
Matlab/Simulink knowledge is recommended for the exercises.
Form of evaluation: Individual evaluation of the course participant will be performed on a basis of:
Attendance rate (5%)
Mini-project (95%)
Course lecturers will design three mini-projects for the Ph.D. course. Each student will be assigned with or select a specific mini-project within the lectured topics, where the students should model the system, design the controllers, and perform simulations. Students are required to finalize the mini-projects within three weeks after the course by submitting a formal technical report with simulation results, which will be assessed by the lecturers in two weeks.
Link: http://www.et.aau.dk/phd/phd-courses/
Organizer: Associate Professor Tomislav Dragičević, e-mail: tdr@et.aau.dk
Lecturers: Associate Professor Tomislav Dragičević - Aalborg University, Associate Professor Ulrik Nyman Aalborg University
ECTS: 3
Time: 29-31 January 2019
Place:
Zip code:
City:
Number of seats: 30
Deadline: 8. January 2019
Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
Description: Model Predictive Control (MPC) is a conceptually simple yet powerful methodology to control power converters and electric drives. It has many advantages over traditional linear controllers including (i) faster response, (ii) high robustness to parameter variation (iii) explicit multivariable control accounting for the process and actuator constraints. The advances in processing power of digital signal processors have recently promoted MPC into the first commercial applications, which opened a door towards improved performance and efficiency of power electronic converters and drives demanded by the evolving industry applications. This course aims to provide the fundamentals required to understand, design and implement MPC to power electronic converters used for a variety of applications including grid-connected converters, drives and microgrids. The motivation is to facilitate wider and faster exploitation of MPC by bridging the gap between theory and successful industrial implementation through cooperation and exchange of experience between academic/research and industrial communities. It is envisioned for both PhD students and practicing engineers.
Some of the course contents are based on recently obtained research results. The main topics are as follows:
Introduction to Model Predictive Control (MPC) for Power Electronic Systems and Drives
Power Converter Modelling Fundamentals and Discretization
Finite-Control-Set Model Predictive Control (FCS-MPC) Principle
Periodic and Dead-Beat Control Principles
Quantitative Performance Evaluation of the FCS-MPC
Application Example: FCS-MPC in 2-level, 3 phase Voltage Source Converter for AC microgrids
Laboratory Exercises (Simulation + Laboratory Demonstration
Prerequisites: General knowledge in electrical AC circuits and electrical power engineering, preferably background at the graduate level in power electronics.
Matlab/Simulink knowledge is recommended for the exercises.
Form of evaluation: Individual evaluation of the course participant will be performed on a basis of:
Attendance rate (5%)
Mini-project (95%)
Course lecturers will design three mini-projects for the Ph.D. course. Each student will be assigned with or select a specific mini-project within the lectured topics, where the students should model the system, design the controllers, and perform simulations. Students are required to finalize the mini-projects within three weeks after the course by submitting a formal technical report with simulation results, which will be assessed by the lecturers in two weeks.
Link: http://www.et.aau.dk/phd/phd-courses/
Organizer: Associate Professor Tomislav Dragičević, e-mail: tdr@et.aau.dk
Lecturers: Associate Professor Tomislav Dragičević - Aalborg University, Associate Professor Ulrik Nyman Aalborg University
ECTS: 3
Time: 29-31 January 2019
Place:
Zip code:
City:
Number of seats: 30
Deadline: 8. January 2019
Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Tomislav Dragicevic