System level synthesis enables improved robust MPC formulations by allowing for joint optimization of the nominal trajectory and controller. This paper introduces a tailored algorithm for solving the corresponding disturbance feedback optimization problem for linear time-varying systems. The proposed algorithm iterates between optimizing the controller and the nominal trajectory while converging q-linearly to an optimal solution. We show that the controller optimization can be solved through Riccati recursions leading to a horizon-length, state, and input scalability of O(N^2(n_x^3+n_u^3)) for each iterate. On a numerical example, the proposed algorithm exhibits computational speedups by a factor of up to 10^3 compared to general-purpose commercial solvers.

ISSN:2405-8963