Robust Control Contraction Metrics: A Convex Approach to Nonlinear State-Feedback <inline-formula> <tex-math notation="LaTeX">${H}^\infty$ </tex-math> </inline-formula> Control

Abstract

This letter proposes a new method for robust state-feedback control design for nonlinear systems. We introduce robust control contraction metrics (RCCM), extending the method of control contraction metrics from stabilization to disturbance attenuation and robust control. An RCCM is a Riemannian metric that verifies differential $L^{2}$ -gain bounds in closed-loop, and guarantees robust stability of arbitrary trajectories via small gain arguments. Numerical search for such a metric can be transformed to a convex optimization problem. We also show that the associated Riemannian energy can be used as a robust control Lyapaunov function. A simple computational example based on jet-engine surge illustrates the approach.