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Fast model predictive control: an approach to improve the performance of power electronics systems


S. Mariéthoz

Supélec, Paris, France

Model predictive control is a receding horizon control scheme where the optimal control action is found by solving a constrained finite time optimal control problem at each sampling instant. The computational complexity depends on the problem class that is characterized by the model class, the cost function class and the type of constraints. For piecewise affine models with linear or quadratic costs and piecewise affine constraints the optimal control law can be synthesized off-line and implemented very efficiently using binary searchtrees. The presentation is illustrated by several application examples in power electronics where the concepts have been successfully applied, enabling improved system performance.

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S. Mariéthoz

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