.png){kind=icon}
.png){kind=icon}
Return
A robust stability framework for LTI systems with time-varying sampling
.png){kind=icon}
OA
AI
DOI：10.1016/j.automatica.2015.01.035.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This work aims at enlarging the sampling intervals in several state feedback control situations by designing a sampling map in the state space. We consider the case of linear time invariant (LTI) systems with state-bounded perturbations, and guarantee their exponential stability for a chosen decay-rate. The approach is based on linear matrix inequalities (LMIs) obtained thanks to Lyapunov-Razumikhin stability conditions and convexification arguments. First, it enables to optimize the lower-bound of the sampling maps by computing the adequate Lyapunov-Razumikhin function. This result can be interpreted as a robust stability analysis with respect to arbitrary time-varying sampling intervals, which may be useful in the case of uncontrolled sampling, or in the presence of phenomenon such as sampling jitter. Then, the obtained results are extended to design the sampling map in three dynamic sampling control situations: event-triggered control, self-triggered control, and state-dependent sampling. The results are illustrated with a numerical example from the literature. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
State-dependent sampling
Self-triggered control
Event-triggered control
Time-varying sampling
Linear matrix inequality
Lyapunov-Razumikhin
Convex embedding
Sampled-data control
Sampling jitter
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.