Discrete-time feedback linearization control for nonsmooth constrained optimization

We propose a discrete-time feedback linearization control approach to solve nonsmooth linearly constrained composite optimization problems. By using proximal operators, we construct a dynamical system whose equilibria correspond to the stationary points of the optimization problem. Interpreting the Lagrange multipliers as control inputs, we employ feedback linearization control to steer the obtained dynamical system to a stable equilibrium. We analyze the convergence of the resulting closed-loop system both in the strongly convex setting and under the Polyak--\L{}ojasiewicz condition. Finally, we illustrate the applicability of the approach through numerical experiments.