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Found 6 papers, 0 papers with code
Predictive stability filters for nonlinear dynamical systems affected by disturbances
Predictive safety filters provide a way of projecting potentially unsafe inputs, proposed, e. g. by a human or learning-based controller, onto the set of inputs that guarantee recursive state and input constraint satisfaction by leveraging model predictive control techniques.
Approximate Predictive Control Barrier Functions using Neural Networks: A Computationally Cheap and Permissive Safety Filter
A predictive control barrier function (PCBF) based safety filter is a modular framework to verify safety of a control input by predicting a future trajectory.
Generalised Regret Optimal Controller Synthesis for Constrained Systems
This paper presents a synthesis method for the generalised dynamic regret problem, comparing the performance of a strictly causal controller to the optimal non-causal controller under a weighted disturbance.
A System Level Approach to Regret Optimal Control
We present an optimisation-based method for synthesising a dynamic regret optimal controller for linear systems with potentially adversarial disturbances and known or adversarial initial conditions.
Adaptive Model Predictive Safety Certification for Learning-based Control -- Extended Version
By continuously connecting the current system state with a safe terminal set using a robust tube, safety can be ensured.
Robust Adaptive Model Predictive Control of Quadrotors
To the best of our knowledge this is the first time that RAMPC has been applied in practice using a state space formulation.
