Abstract: Since the beginning of the current millennium, Model Predictive Control (MPC) started gaining ever-increasing interest within the power electronics and electrical drives community. MPC is an uprising method that has been shown to exhibit superior dynamic performance in comparison to the incumbent classical PI controllers. Nonetheless, MPC possesses its own set of challenges, leading amongst of which are identifying the accurate mathematical models and tackling its computational complexity.

This talk will introduce MPC and its potential as well as its current challenges for electrical drives. Moreover, the use of artificial intelligence algorithms to alleviate some of MPC’s shortcomings is outlined. To this end, experimental results from a synchronous machine testbench are presented.

Biography: Issa Hammoud (Student Member, IEEE) received the M.Sc. degree in power engineering with distinction from the Technical University of Munich, Germany, where he is currently a PhD candidate at the Chair of High-Power Converter Systems. He conducted his doctoral research in industry at the Powertrain Mechatronics Control Engineering Excellence Cluster, IAV GmbH, Gifhorn, Germany. He recently started at Robert Bosch GmbH, Stuttgart, Germany, in the field of control of electrical drives. Mr. Hammoud received the best paper awards at the Fifth and Sixth International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) in 2019 and 2021, respectively.

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