Results 181 to 190 of about 158,055 (244)

Sliding Mode Control in Aerospace Applications: A Survey

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Sliding mode control (SMC) enjoys robustness to matched and unmatched (in the case of minimum phase input‐output dynamics) bounded perturbations, and finite time convergence. Second‐order and higher‐order sliding mode control systems (2‐SMC/HOSMC) retain all the advantages of sliding mode control, but in addition can be applied to systems of ...
Yuri Shtessel, Christopher Edwards
wiley   +1 more source

Safe Stabilization Using Non‐Smooth Control Lyapunov Barrier Function

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper addresses the challenge of safe stabilization, ensuring the system state reaches the origin while avoiding unsafe state regions. Existing approaches that rely on smooth Lyapunov barrier functions often fail to guarantee a feasible controller. To overcome this limitation, we introduce the non‐smooth control Lyapunov barrier function (
Jianglin Lan   +3 more
wiley   +1 more source

The role of identification in data‐driven policy iteration: A system theoretic study

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley   +1 more source

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

open access: yesResponsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen   +8 more
wiley   +1 more source

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