Safety-Critical Control for Nonlinear Systems With Complex Input Constraints

• 成果类型: Article
• 署名作者: Deng, Yaosheng; Ogura, Masaki; Bai, Yang; Wang, Yujie; Feroskhan, Mir
• 署名单位: Nanyang Technological University; Hiroshima University; University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3570826
• 发表日期: 2025
• 页码: 7016-7023
• 关键词: safety; Nonlinear systems; vectors; Time-varying systems; quadratic programming; Lyapunov methods; Transforms; training; system performance; solids; Control barrier function (CBF); input constraint; quadratic programming (QP)

摘要

In this article, we propose a novel control barrier function (CBF)-based controller for nonlinear systems with complex, time-varying input constraints. To deal with these constraints, we introduce an auxiliary control input to transform the original system into an augmented one, thus reformulating the constrained-input problem into a constrained-output one. This transformation simplifies the quadratic programming formulation and enhances compatibility with the CBF framework. As a result, the proposed method can systematically address the complex, time-varying, and state-dependent input constraints. The efficacy of the proposed approach is validated using numerical examples.