Sep 20, 2024 ， Using the Alternating Direction Method of Multipliers (ADMM), several variations of constrained DDP have been presented such as in Sindhwani et al.
Oct 3, 2024 ， This thesis is concerned with the design of distributed algorithms for solving optimization problems. The particular scenario we consider is a network with ...
Sep 23, 2024 ， This paper reviews the application of distributed model predictive control (DMPC) for autonomous intelligent systems (AIS) with unmanned aerial vehicles ...
Oct 2, 2024 ， This paper presents a contact-implicit model predictive control (MPC) framework for the real-time discovery of multi-contact motions, without predefined contact ...
Oct 2, 2024 ， The alternating direction method of multipliers (ADMM) offers significant benefits for constrained machine learning tasks by breaking down complex optimization ...
Sep 15, 2024 ， We develop time-parallel second-order solvers based on interior point methods and the alternating direction method of multipliers, leveraging fast convergence ...
5 days ago ， We settled on developing a convex model predictive control solver based on the alternating direction method of multipliers. Convex MPC solvers are limited ...
Oct 1, 2024 ， Optimally linearizing the alternating direction method of multipliers for convex programming. Computational Optimization and Applications, Vol. 75, No. 2 ...
3 days ago ， We develop a new method which extends dynamic mode decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, ...
Sep 21, 2024 ， ... Model Predictive Control Abstract: This paper presents a model predictive control (MPC) method for redundant robots controlling multiple hierarchical tasks ...
