The analysts working on AI projects have a crucial question: How will the interventions brought about by the AI cause the desired outcomes? To date, only about 20% of companies have managed to scale ...
Abstract: Model predictive control has attracted much attention in electric drives, but its parameter sensitivity on explicit models poses inherent challenges to the further application. This paper ...
Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...
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