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Model Predictive Control in Power Electronics


S. Mariéthoz

University of Missouri-Rolla, IEEECIS/IAS/IEEE Seminar

In the context of control, hybrid systems combine continuous and discrete dynamics. Model Predictive Control (MPC) is a technique where the control objective is expressed as a constrained optimization problem. The cost function is evaluated over a receding horizon and based on the evolution of the system that is evaluated through a discrete model. Model Predictive Control is very well suited to solve hybrid control problems that include constraints. Power converters are typical hybrid systems. Their behavior is continuous between the switches'commutation and displays discrete abrupt changes following each commutation. Application of MPC in power electronics started recently, as in most cases the optimization process requires intensive computations that are/were not compatible with the very short sampling time of power electronic systems. Explicit model predictive control has been one of the main enabling factor for the technique expansion to power electronics. It is applicable for a large number of problems and requires a very limited computational power. The optimization problem is solved off-line, the on-line task only amounts to obtain the control input through a look-up table. The talk will present some aspects of Model Predictive Control through some selected power electronics applications.

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