A min-max robust DDPC method is introduced via uncertainty sets derived from non-unique behavioral solutions, yielding convex reformulations, feedback extensions, and performance guarantees under bounded noise.
Fast data- driven model predictive control strategy for connected and automated vehicles
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On Min-Max Robust Data-Driven Predictive Control Considering Non-Unique Solutions to Behavioral Representation
A min-max robust DDPC method is introduced via uncertainty sets derived from non-unique behavioral solutions, yielding convex reformulations, feedback extensions, and performance guarantees under bounded noise.