no code implementations • 22 Jan 2024 • Wei Ren, Wei Wang, Zhuo-Rui Pan, Xi-Ming Sun, Andrew R. Teel, Dragan Nesic
Next, the proposed scheduling protocol is embedded into the closed-loop system, which leads to a stochastic hybrid model for NCSs with random packet dropouts.
no code implementations • 4 Apr 2022 • Justin H. Le, Andrew R. Teel
High-order tuners are algorithms that show promise in achieving greater efficiency than classic gradient-based algorithms in identifying the parameters of parametric models and/or in facilitating the progress of a control or optimization algorithm whose adaptive behavior relies on such models.
no code implementations • 4 May 2021 • Giordano Scarciotti, Andrew R. Teel
In this paper we study the problem of model reduction by moment matching for stochastic systems.
no code implementations • 23 Apr 2021 • Justin H. Le, Andrew R. Teel
Soft-reset controllers are introduced as a way to approximate hard-reset controllers.
no code implementations • 21 Apr 2021 • Matina Baradaran, Justin H. Le, Andrew R. Teel
Convex optimization challenges are currently pervasive in many science and engineering domains.
no code implementations • 29 Sep 2020 • Justin H. Le, Andrew R. Teel
Momentum methods for convex optimization often rely on precise choices of algorithmic parameters, based on knowledge of problem parameters, in order to achieve fast convergence, as well as to prevent oscillations that could severely restrict applications of these algorithms to cyber-physical systems.