2 research outputs found

    Safety-Critical Event Triggered Control via Input-to-State Safe Barrier Functions

    Full text link
    The efficient utilization of available resources while simultaneously achieving control objectives is a primary motivation in the event-triggered control paradigm. In many modern control applications, one such objective is enforcing the safety of a system. The goal of this paper is to carry out this vision by combining event-triggered and safety-critical control design. We discuss how a direct transcription, in the context of safety, of event-triggered methods for stabilization may result in designs that are not implementable on real hardware due to the lack of a minimum interevent time. We provide a counterexample showing this phenomena and, building on the insight gained, propose an event-triggered control approach via Input to State Safe Barrier Functions that achieves safety while ensuring that interevent times are uniformly lower bounded. We illustrate our results in simulation.Comment: 6 pages, 2 figures, submitted to L-CSS + CDC 202

    Resource-Aware Discretization of Accelerated Optimization Flows

    Full text link
    This paper tackles the problem of discretizing accelerated optimization flows while retaining their convergence properties. Inspired by the success of resource-aware control in developing efficient closed-loop feedback implementations on digital systems, we view the last sampled state of the system as the resource to be aware of. The resulting variable-stepsize discrete-time algorithms retain by design the desired decrease of the Lyapunov certificate of their continuous-time counterparts. Our algorithm design employs various concepts and techniques from resource-aware control that, in the present context, have interesting parallelisms with the discrete-time implementation of optimization algorithms. These include derivative- and performance-based triggers to monitor the evolution of the Lyapunov function as a way of determining the algorithm stepsize, exploiting sampled information to enhance algorithm performance, and employing high-order holds using more accurate integrators of the original dynamics. Throughout the paper, we illustrate our approach on a newly introduced continuous-time dynamics termed heavy-ball dynamics with displaced gradient, but the ideas proposed here have broad applicability to other globally asymptotically stable flows endowed with a Lyapunov certificate
    corecore