Robust and Exponential Stability in Barrier-Certified Systems via Contracting Piecewise Smooth Dynamics

In this letter, we address the critical trade-off between safety and performance in control systems by establishing the contractivity of a class of nonlinear systems driven by control barrier function (CBF)-based online feedback optimization. First, we derive a closed-form solution for the control system driven by a CBF-based controller with vector-valued safety constraints. Next, we introduce sufficient design conditions based on the properties of a baseline controller and CBF parameters to ensure both safety and contractivity of the closed-loop system. Under these conditions, we demonstrate the existence of an exponentially stable equilibrium within the safe set and provide an explicit term for the rate of convergence. Building upon these results, we propose a feedback motion planning algorithm that guarantees a global region of attraction within non-convex search areas through a tree of contractive controllers. The contractive nature of our approach ensures robustness against perturbations, making it suitable for dynamic and uncertain environments.