Dual-Regularized Riccati Recursions for Interior-Point Optimal Control
Optimization and Control
2026-02-26 v5 Mathematical Software
Robotics
Systems and Control
Systems and Control
Abstract
We derive closed-form extensions of Riccati's recursions (both sequential and parallel) for solving dual-regularized LQR problems. We show how these methods can be used to solve general constrained, non-convex, discrete-time optimal control problems via a regularized interior point method, while guaranteeing that each primal step is a descent direction of an Augmented Barrier-Lagrangian merit function. We provide MIT-licensed implementations of our methods in C++ and JAX.
Keywords
Cite
@article{arxiv.2509.16370,
title = {Dual-Regularized Riccati Recursions for Interior-Point Optimal Control},
author = {João Sousa-Pinto and Dominique Orban},
journal= {arXiv preprint arXiv:2509.16370},
year = {2026}
}