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Disturbance-adaptive MPC with Bounds on Average Constraint Violations
US & West ·
A new DAD-MPC framework for stochastic systems adapts the disturbance model based on measured constraint violations. The method guarantees recursive feasibility and asymptotic bounds on average violations even with an inaccurate model, enabling data-driven approaches like conformal prediction.
Why it matters
Important for constrained control under uncertainty, relevant to energy and industry.
At the 20th anniversary of the Korea-Africa Economic Cooperation (KOAFEC), Korea and Africa charted a new course for cooperation on artificial intelligence and digital infrastructure. Details of agreements were not disclosed.
