Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Time-Domain Interpretation of PD Control

Time-Domain Interpretation of PD Control

Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...

Understanding Deception

Understanding Deception

Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...

Frequency-Domain Interpretation of PD Control

Frequency-Domain Interpretation of PD Control

Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...

Control Systems

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

Transfer Function in Control Systems

Transfer Function in Control Systems

The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
To derive the transfer function, consider a general nth-order linear time-invariant...

Control System Problem

Control System Problem

In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Glucocorticoid Steroid and Alendronate Treatment Alleviates Dystrophic Phenotype with Enhanced Functional Glycosylation of α-Dystroglycan in Mouse Model of Limb-Girdle Muscular Dystrophy with FKRPP448L Mutation.

The American journal of pathology·2016

Same author

Exogenous H2S contributes to recovery of ischemic post-conditioning-induced cardioprotection by decrease of ROS level via down-regulation of NF-κB and JAK2-STAT3 pathways in the aging cardiomyocytes.

Cell & bioscience·2016

Same author

Common susceptibility variants are shared between schizophrenia and psoriasis in the Han Chinese population.

Journal of psychiatry & neuroscience : JPN·2016

Same author

Phylogenetic relationship of two popular edible Pleurotus in China, Bailinggu (P. eryngii var. tuoliensis) and Xingbaogu (P. eryngii), determined by ITS, RPB2 and EF1α sequences.

Molecular biology reports·2016

Same author

[Effect of ginsenoside total saponinon on regulation of P450 of livers of rats after γ-ray irradiation].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2016

Same author

Lipid-polymer hybrid nanoparticles for the delivery of gemcitabine.

Journal of controlled release : official journal of the Controlled Release Society·2016

Search research articles

Related Experiment Video

Updated: Jan 8, 2026

A Protocol for Real-time 3D Single Particle Tracking

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Peak-to-peak secure tracking control for distributed networked control systems under TOD protocol and deception

Fang Zhao¹, Bo Wu¹, Xisheng Zhan¹

¹College of Electrical Engineering and Automation, Hubei Normal University, Huangshi, 435002, China.

ISA Transactions

|December 16, 2025

Summary

This study addresses secure tracking control for networked systems facing deception attacks. A new controller ensures stability and performance despite communication vulnerabilities using the try-once-discard protocol.

Keywords:

Deception attacks Distributed networked control systems Peak-to-peak performance TOD protocol Tracking control

More Related Videos

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Jan 8, 2026

A Protocol for Real-time 3D Single Particle Tracking

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Control Engineering
Networked Systems Security
Cyber-Physical Systems

Background:

Distributed networked control systems (DNCS) are susceptible to deception attacks.
The try-once-discard (TOD) protocol is used for signal transmission but can be compromised.
Ensuring system stability and performance under random attacks is a significant challenge.

Purpose of the Study:

To investigate the peak-to-peak secure tracking control problem for DNCS.
To design a mode-dependent controller resilient to deception attacks.
To guarantee system stability and prescribed peak-to-peak performance.

Main Methods:

Utilized the try-once-discard (TOD) protocol for signal transmission.
Characterized deception attacks using a Bernoulli binomial distribution.
Derived sufficient conditions for controller design via linear matrix inequalities (LMIs).

Main Results:

Developed a mode-dependent controller for secure tracking control.
Demonstrated that the proposed controller ensures system stability and peak-to-peak performance.
Validated the controller's effectiveness through simulation examples.

Conclusions:

The proposed method effectively addresses peak-to-peak secure tracking control in DNCS under deception attacks.
LMIs provide a robust framework for designing secure controllers for networked systems.
The research contributes to enhancing the security and reliability of cyber-physical systems.