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Controller design for nonlinear systems with Control Lyapunov Function (CLF)based quadratic programs has recently been successfully applied to a diverseset of difficult control tasks. These existing formulations do not address thegap between design with continuous time models and the discrete time sampledimplementation of the resulting controllers, often leading to poor performanceon hardware platforms. We propose an approach to close this gap by synthesizingsampled-data counterparts to these CLF-based controllers, specified asquadratically constrained quadratic programs (QCQPs). Assuming feedbacklinearizability and stable zero-dynamics of a system's continuous time model,we derive practical stability guarantees for the resulting sampled-data system.We demonstrate improved performance of the proposed approach over continuoustime counterparts in simulation.

Sampled-Data Stabilization with Control Lyapunov Functions via Quadratically Constrained Quadratic Programs