54 citations · 217 across the 13 of their papers we have counts for
5 papers · 1 filter
Regret Bounds for Adaptive Nonlinear Control
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
We study the problem of adaptively controlling a known discrete-time nonlinear system subject to unmodeled disturbances. We prove the first finite-time regret bounds for adaptive n…
Safely Learning Dynamical Systems from Short Trajectories
Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani +1
A fundamental challenge in learning to control an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. In this work, we formulat…
Learning Hybrid Control Barrier Functions from Data
Lars Lindemann, Haimin Hu, Alexander Robey +4
Motivated by the lack of systematic tools to obtain safe control laws for hybrid systems, we propose an optimization-based framework for learning certifiably safe control laws from…
Learning Stability Certificates from Data
Nicholas M. Boffi, Stephen Tu, Nikolai Matni +2
Many existing tools in nonlinear control theory for establishing stability or safety of a dynamical system can be distilled to the construction of a certificate function that guara…
Learning Control Barrier Functions from Expert Demonstrations
Alexander Robey, Haimin Hu, Lars Lindemann +4
Inspired by the success of imitation and inverse reinforcement learning in replicating expert behavior through optimal control, we propose a learning based approach to safe control…