Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems

AS Leong, A Ramaswamy, DE Quevedo, H Karl, L Shi - Automatica, 2020 - Elsevier
In many cyber–physical systems, we encounter the problem of remote state estimation of
geographically distributed and remote physical processes. This paper studies the …

State-aware real-time tracking and remote reconstruction of a Markov source

M Salimnejad, M Kountouris… - … of Communications and …, 2023 - ieeexplore.ieee.org
The problem of real-time remote tracking and reconstruction of a two-state Markov process is
considered here. A transmitter sends samples from an observed information source to a …

Real-time remote estimation with hybrid ARQ in wireless networked control

K Huang, W Liu, M Shirvanimoghaddam… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Real-time remote estimation is critical for mission-critical applications including industrial
automation, smart grid and tactile Internet. In this paper, we propose a hybrid automatic …

Real-time reconstruction of markov sources and remote actuation over wireless channels

M Salimnejad, M Kountouris… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this work, we study the real-time tracking and reconstruction of an information source with
the purpose of actuation. A device monitors the state of the information source and transmits …

Deep learning for wireless networked systems: A joint estimation-control-scheduling approach

Z Zhao, W Liu, DE Quevedo, Y Li… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Wireless-networked control system (WNCS) connecting sensors, controllers, and actuators
via wireless communications is a key enabling technology for highly scalable and low-cost …

Remote state estimation with smart sensors over Markov fading channels

W Liu, DE Quevedo, Y Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We consider a fundamental remote state estimation problem of discrete-time linear time-
invariant (LTI) systems. A smart sensor forwards its local state estimate to a remote estimator …

Transmission scheduling for multi-process multi-sensor remote estimation via approximate dynamic programming

A Forootani, R Iervolino, M Tipaldi, S Dey - Automatica, 2022 - Elsevier
In this paper, we consider a remote estimation problem where multiple dynamical systems
are observed by smart sensors, which transmit their local estimates to a remote estimator …

Quasisynchronization for neural networks with partial constrained state information via intermittent control approach

H Rao, L Zhao, Y Xu, Z Huang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This work addresses quasisynchronization (QS) of the master–slave (MS) neural networks
(NNs) with mismatched parameters. The logarithmic quantizer and the round-robin protocol …

Multisensor scheduling for remote state estimation over a temporally correlated channel

J Wei, D Ye - IEEE Transactions on Industrial Informatics, 2022 - ieeexplore.ieee.org
This article studies multisensor scheduling for remote state estimation in cyber-physical
systems. We consider that each sensor monitors a dynamic process and sends its data to …

Learning-based DoS attack power allocation in multiprocess systems

M Huang, K Ding, S Dey, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
We study the denial-of-service (DoS) attack power allocation optimization in a multiprocess
cyber–physical system (CPS), where sensors observe different dynamic processes and …