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We present a novel model predictive control (MPC) scheme with relaxedstability criteria, based on the idea of generalized discrete-time controlLyapunov functions. Most notably, this scheme allows for implementing aflexible number of control inputs in each iteration, while guaranteeingrecursive feasibility and stability. The advantages of our flexible-stepimplementation are demonstrated on nonholonomic systems, where the one-stepstandard implementation may suffer from lack of asymptotic convergence.

Flexible-step Model Predictive Control based on generalized Lyapunov functions