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math.OC2025
Value Function Approximation for Nonlinear MPC: Learning a Terminal Cost Function with a Descent Property
T. M. J. T. Baltussen, C. A. Orrico, A. Katriniok +2
We present a novel method to synthesize a terminal cost function for a nonlinear model predictive controller (MPC) through value function approximation using supervised learning. E…
math.OC2025
Counterexample-Guided Synthesis of Robust Discrete-Time Control Barrier Functions
Erfan Shakhesi, Alexander Katriniok, W. P. M. H. Heemels
Learning-based methods have gained popularity for training candidate Control Barrier Functions (CBFs) to satisfy the CBF conditions on a finite set of sampled states. However, sinc…