290 citations · 1.9k across the 78 of their papers we have counts for
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Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty
Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean +3
Modern nonlinear control theory seeks to endow systems with properties such as stability and safety, and has been deployed successfully across various domains. Despite this success…
A Control Barrier Perspective on Episodic Learning via Projection-to-State Safety
Andrew J. Taylor, Andrew Singletary, Yisong Yue +1
In this paper we seek to quantify the ability of learning to improve safety guarantees endowed by Control Barrier Functions (CBFs). In particular, we investigate how model uncertai…
Learning for Safety-Critical Control with Control Barrier Functions
Andrew Taylor, Andrew Singletary, Yisong Yue +1
Modern nonlinear control theory seeks to endow systems with properties of stability and safety, and have been deployed successfully in multiple domains. Despite this success, model…
A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability
Andrew J. Taylor, Victor D. Dorobantu, Meera Krishnamoorthy +3
The goal of this paper is to understand the impact of learning on control synthesis from a Lyapunov function perspective. In particular, rather than consider uncertainties in the f…
Barrier Certificates for Assured Machine Teaching
Mohamadreza Ahmadi, Bo Wu, Yuxin Chen +2
Machine teaching can be viewed as optimal control for learning. Given a learner's model, machine teaching aims to determine the optimal training data to steer the learner towards a…