Learning-based Prescribed-Time Safety for Control of Unknown Systems with Control Barrier Functions
arxiv(2024)
摘要
In many control system applications, state constraint satisfaction needs to
be guaranteed within a prescribed time. While this issue has been partially
addressed for systems with known dynamics, it remains largely unaddressed for
systems with unknown dynamics. In this paper, we propose a Gaussian
process-based time-varying control method that leverages backstepping and
control barrier functions to achieve safety requirements within prescribed time
windows. It can be used to keep a system within a safe region or to make it
return to a safe region within a limited time window. These properties are
cemented by rigorous theoretical results. The effectiveness of the proposed
controller is demonstrated in a simulation of a robotic manipulator.
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