制御バリア関数による安全臨界制御：階層最適化フレームワーク
Safety-critical Control with Control Barrier Functions: A Hierarchical Optimization Framework
制御バリア関数（CBF）を用いた安全臨界システム設計において、多目的最適化問題を安全性優先で入れ子型の部分問題に分解する階層最適化フレームワークを提案し、既存のQPベース手法より安全性・実現可能性・収束速度で優れることを示した。
著者: Junjun Xie, Liang Hu, Jiahu Qin, Jun Yang, Huijun Gao
分類: math.OC, cs.RO
原文アブストラクト
The control barrier function (CBF) has become a fundamental tool in safety-critical systems design since its invention. Typically, the quadratic optimization framework is employed to accommodate CBFs, control Lyapunov functions (CLFs), other constraints and nominal control design. However, the constrained optimization framework involves hyper-parameters to tradeoff different objectives and constraints, which, if not well-tuned beforehand, impact system performance and even lead to infeasibility. In this paper, we propose a hierarchical optimization framework that decomposes the multi-objective optimization problem into nested optimization sub-problems in a safety-first approach. The new framework addresses potential infeasibility on the premise of ensuring safety and performance as much as possible and applies easily in multi-certificate cases. With vivid visualization aids, we systematically analyze the advantages of our proposed method over existing QP-based ones in terms of safety, feasibility and convergence rates. Moreover, two numerical examples are provided that verify our analysis and show the superiority of our proposed method.
