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High-Speed Online MPC Based on a Fast Gradient Method Applied to Power Converter Control


S. Richter

American Control Conference, Baltimore, US

Bounding the computational complexity of an online optimization method in a real-time environment with hard time constraints is a challenging problem. This paper considers a new solution approach based on a fast gradient method in the context of Model Predictive Control (MPC) of power converters. Different from other solution methods that either do not allow for bounding the computational effort at all or provide bounds that are far off from practically observed bounds, the fast gradient method is shown to provide easy to compute and meaningful bounds that can further be decreased by means of a pre-conditioning technique. We report an implementation of this method on an industrial-type digital signal processor with integer arithmetics and show that runtimes are in the order of tens of us using less than one kByte of memory. Finally, we not only prove feasibility of the new method but also show that we outperform control approaches that are based on explicit MPC.


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M. Morari

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