Confidence-Aware Safe and Stable Control of Control-Affine Systems
This work designs safe and stable control for nonlinear systems using output feedback while improving state estimation confidence. It uses an Extended Kalman Filter to estimate states and a confidence metric derived from the error covariance matrix P(t). The core contribution is an optimization approach that synthesizes control inputs by balancing tracking performance with minimizing future uncertainty, ensuring both safety and stability.