Summary
While safety is often critical for nonlinear systems, guaranteeing safety should not hinder their performance drastically. Various approaches have been considered in the literature to achieve both safety and performance for nonlinear systems by means of control, and the use of safety filters has been gaining traction thanks to its flexibility. The safety filter safeguards an already well-tuned performance-based controller by minimal intervention only when necessary such that a safety constraint is satisfied. A convenient tool to establish this safety constraint is control barrier functions (CBFs), which provide the formal safety guarantees for the underlying nonlinear dynamics through a Lyapunov-like condition. The accuracy of the CBF-based safety constraint may reduce in the presence of uncertainty in the system model such as external disturbances. In this manuscript, we discuss the design steps of a robust safety filter, which leads to an easy-to-implement and easy-to-interpret control scheme to provide safety for nonlinear systems under uncertainty. We take a worst-case type of approach to accommodate bounded disturbances, and we use a modification to mitigate the unnecessary conservativeness. Concepts are demonstrated and evaluated on a example with a swing.
