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Related Concept Videos

Control Systems01:10

Control Systems

1.7K
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...
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Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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Open and closed-loop control systems01:17

Open and closed-loop control systems

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Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
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Control System Problem01:21

Control System Problem

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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...
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Control Systems: Applications01:25

Control Systems: Applications

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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
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Radial System Protection01:23

Radial System Protection

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Radial systems employ time-delay overcurrent relays to reduce load interruptions. When a fault occurs, the nearest breaker opens first, while upstream breakers remain closed due to longer delay settings. This approach ensures minimal disruption to the rest of the system.
In a radial system with a fault downstream of the third breaker, ideally, only the third breaker will open, isolating the fault and interrupting the load connected beyond it. The second breaker has a longer delay setting,...
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Related Experiment Video

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Resilient Tracking Control of Networked Control Systems Under Cyber Attacks.

Eman Mousavinejad, Xiaohua Ge, Qing-Long Han

    IEEE Transactions on Cybernetics
    |November 15, 2019
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    Summary

    This study presents resilient tracking control for networked systems against cyber attacks. It ensures system state accuracy despite deception and denial-of-service attacks using set-membership control and estimation.

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    Area of Science:

    • Control Systems Engineering
    • Cybersecurity
    • Networked Systems

    Background:

    • Networked control systems (NCS) are vulnerable to cyber attacks targeting communication channels.
    • Active adversaries can launch deception and denial-of-service (DoS) attacks to degrade system performance.
    • Ensuring system resilience and tracking accuracy under attack is a critical challenge.

    Purpose of the Study:

    • To develop a resilient tracking control strategy for NCS under sophisticated cyber attacks.
    • To guarantee that the system's true state remains within a defined set of the reference state, despite attacks and noise.
    • To provide a robust state estimation method that secures estimates against deception attacks.

    Main Methods:

    • Introduced a resilient set-membership tracking control concept.
    • Developed a resilient set-membership estimation strategy for untrusted state information.
    • Utilized recursive linear matrix inequalities (LMIs) for convex optimization to determine controller and estimator gains.
    • Employed recursive computation of reference state and confidence state estimation ellipsoids.

    Main Results:

    • The proposed method guarantees the system's true state resides within a bounding ellipsoidal set of the reference state.
    • Resilient state estimates are secured against deception attacks.
    • A convex optimization algorithm based on recursive LMIs effectively computes gain parameters.
    • The approach demonstrated effectiveness in an Internet-based three-tank system simulation.

    Conclusions:

    • The presented resilient set-membership tracking control and estimation strategies effectively mitigate cyber attacks in NCS.
    • The method ensures robust tracking performance and state estimation integrity.
    • The proposed optimization approach provides a systematic way to design resilient controllers and estimators for NCS.