aiqbench analysis
This research advances the theoretical framework of safety-critical control systems by introducing novel high-order functions, which are essential for developing robust AI agents operating in dynamic physical environments. By explicitly addressing compatibility between stabilization and safety constraints, these methods provide a rigorous foundation for deploying autonomous robotics with guaranteed reliability.
Optimal Safety Control using High-Order Control Barrier Functions
arXiv:2607.17032v1 Announce Type: cross Abstract: This paper investigates the optimal safety control problem of nonlinear control systems by proposing novel high-order control barrier functions (HOCBFs). Different from zeroing HOCBFs, two novel HOCBFs are derived and the safety controllers are designed in an explicit way. Next, we implement vector Lyapunov function approach to propose a novel high-order control Lyapunov function (HOCLF) for the stabilization control problem. The relations between the proposed and existing HOCBFs are discussed. Afterwards, the compatibility of the proposed HOCLF and HOCBF is addressed to guarantee the stabilization and safety control objectives simultaneously, and thus the optimal controller is established. Finally, a numerical example from the navigation problem of quadrotors is presented to illustrate the efficacy of the derived results.
Abstract:This paper investigates the optimal safety control problem of nonlinear control systems by proposing novel high-order control barrier functions (HOCBFs). Different from zeroing HOCBFs, two novel HOCBFs are derived and the safety controllers are designed in an explicit way. Next, we implement vector Lyapunov function approach to propose a novel high-order control Lyapunov function (HOCLF) for the stabilization control problem. The relations between the proposed and existing HOCBFs are discussed. Afterwards, the compatibility of the proposed HOCLF and HOCBF is addressed to guarantee the stabilization and safety control objectives simultaneously, and thus the optimal controller is established. Finally, a numerical example from the navigation problem of quadrotors is presented to illustrate the efficacy of the derived results.
Systems and Control (eess.SY); Robotics (cs.RO)
arXiv:2607.17032 [eess.SY]
(or arXiv:2607.17032v1 [eess.SY] for this version)
https://doi.org/10.48550/arXiv.2607.17032 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 214 words
