Abstract:
Barrier functions have been utilized in guaranteeing safety for control laws, and their coupling with conditions which guarantee that the closed-loop state can be driven ...View moreMetadata
Abstract:
Barrier functions have been utilized in guaranteeing safety for control laws, and their coupling with conditions which guarantee that the closed-loop state can be driven to the origin has also been important for achieving performance objectives. For optimization-based control, approaches have been developed to guarantee safety via barrier functions while simultaneously guaranteeing that a reference or equilibrium can be tracked. One approach has assumed an instantaneous computation of the control action from a quadratic programming-based control law that determines control actions which satisfy a decreasing Lyapunov condition when possible but always satisfy a barrier function-based safety constraint. This approach decouples safety and performance objectives to prefer the safety objective over performance when they conflict. In an alternative approach, a single function is located which, when decreased, guarantees that safety and performance objectives are met simultaneously, and has been implemented within the context of model predictive control. In this work, we discuss connections between barrier function-based and Lyapunov function-based control approaches to maintaining safety.
Published in: 2022 American Control Conference (ACC)
Date of Conference: 08-10 June 2022
Date Added to IEEE Xplore: 05 September 2022
ISBN Information: