Model Predictive Control (MPC) is a conceptually simple yet powerful methodology to control power converters and electric drives. It has many advantages over traditional controllers including its capability to intuitively handle a great variety of control problems by considering different modes of operation and directly incorporating system constraints and additional requirements. MPC minimizes an objective (cost) function subject to the plant model dynamics to obtain the control action. The underlying concepts are intuitive, the resulting controllers are inherently stable and, once calculated, easy to implement.
The advances in processing power of digital signal processors have recently promoted MPC into the first commercial applications, which opened a door toward improved performance and efficiency of power electronic converters and drives demanded by the evolving industry applications.

The motivation for this workshop 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.

The introduction session presents basic principles and methods of MPC with a view toward applications in power electronics and drives. Three different sections focus on different application areas and other important topics. Application examples, including the first commercial application on large variable speed drives (ABB), will be presented and discussed. The difference in control processing between conventional control methods and MPC algorithms will be shown and hints for effective implementation will be shared.

The workshop is chaired by
Prof. Ralph Kennel, Technical University of Munich
Dr. Tobias Geyer, ABB Corporate Research

All presentations and discussions will be in English language.