Impact of Time Delays on Networked Control of Autonomous Systems

2020 ◽  
pp. 151-178
Author(s):  
Prasanna Kolar ◽  
Nicholas Gamez ◽  
Mo Jamshidi
Keyword(s):  
Time Delays ◽  
Autonomous Systems ◽  
Networked Control

Optimal Fault Diagnosis for Networked Control Systems with Large Time-delays and Noises

2012 ◽  
Vol 38 (5) ◽  
pp. 858-864 ◽  
Author(s):  
Juan LI ◽  
You-Gang ZHAO ◽  
Yang YU ◽  
Peng ZHANG ◽  
Hong-Wei GAO
Keyword(s):  
Fault Diagnosis ◽  
Control Systems ◽  
Time Delays ◽  
Large Time ◽  
Networked Control Systems ◽  
Networked Control

scholarly journals How to Simulate Networked Control Systems with Variable Time Delays?

2020 ◽  
Vol 53 (2) ◽  
pp. 3098-3103
Author(s):  
Martin Steinberger ◽  
Markus Tranninger ◽  
Martin Horn ◽  
Karl Henrik Johansson
Keyword(s):  
Control Systems ◽  
Time Delays ◽  
Networked Control Systems ◽  
Networked Control ◽  
Variable Time

scholarly journals Fault Detection for Wireless Networked Control Systems with Stochastic Uncertainties and Multiple Time Delays

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Lina Rong ◽  
Chengda Yu ◽  
Pengfei Guo ◽  
Hui Gao
Keyword(s):  
Fault Detection ◽  
Control Systems ◽  
Time Delays ◽  
Networked Control Systems ◽  
Networked Control ◽  
Linear Matrix ◽  
Multiple Time ◽  
Multiple Time Delays ◽  
System States ◽  
Stochastic Uncertainties

The fault detection problem for a class of wireless networked control systems is investigated. A Bernoulli distributed parameter is introduced in modeling the system dynamics; moreover, multiple time delays arising in the communication are taken into account. The detection observer for tracking the system states is designed, which generates both the state errors and the output errors. By adopting the linear matrix inequality method, a sufficient condition for the stability of wireless networked control systems with stochastic uncertainties and multiple time delays is proposed, and the gain of the fault detection observer is obtained. Finally, an illustrated example is provided to show that the observer designed in this paper tracks the system states well when there is no fault in the systems; however, when fault happens, the observer residual signal rises rapidly and the fault can be quickly detected, which demonstrate the effectiveness of the theoretical results.

Secure Networked Control Systems

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Henrik Sandberg ◽  
Vijay Gupta ◽  
Karl H. Johansson
Keyword(s):  
Control Systems ◽  
Critical Infrastructure ◽  
Networked Control Systems ◽  
Denial Of Service ◽  
Autonomous Systems ◽  
Mitigation Strategies ◽  
Networked Control ◽  
Annual Review ◽  
Publication Date ◽  
Process Industries

Cyber-vulnerabilities are being exploited in a growing number of control systems. As many of these systems form the backbone of critical infrastructure and are becoming more automated and interconnected, it is of the utmost importance to develop methods that allow system designers and operators to do risk analysis and develop mitigation strategies. Over the last decade, great advances have been made in the control systems community to better understand cyber-threats and their potential impact. This article provides an overview of recent literature on secure networked control systems. Motivated by recent cyberattacks on the power grid, connected road vehicles, and process industries, a system model is introduced that covers many of the existing research studies on control system vulnerabilities. An attack space is introduced that illustrates how adversarial resources are allocated in some common attacks. The main part of the article describes three types of attacks: false data injection, replay, and denial-of-service attacks. Representative models and mathematical formulations of these attacks are given along with some proposed mitigation strategies. The focus is on linear discrete-time plant models, but various extensions are presented in the final section, which also mentions some interesting research problems for future work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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