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Related Concept Videos

Control Systems01:10

Control Systems

987
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...
987
Feedback control systems01:26

Feedback control systems

262
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...
262
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

315
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
315
Open and closed-loop control systems01:17

Open and closed-loop control systems

594
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...
594
Controller Configurations01:22

Controller Configurations

79
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
79
Control System Problem01:21

Control System Problem

94
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...
94

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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
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Observer-Based Bounded H∞ Control for Shift-Varying Linear Repetitive Processes With Constrained Bit Rates Over a

Chengyu Yang, Jinling Liang

    IEEE Transactions on Cybernetics
    |March 18, 2025
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    Summary
    This summary is machine-generated.

    This study introduces a novel observer-based bounded H-infinity control for linear repetitive processes (LRPs) over networks with bit rate constraints. The method optimizes bandwidth use and ensures system stability within a finite horizon.

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    Area of Science:

    • Control Systems Engineering
    • Networked Systems
    • Signal Processing

    Background:

    • Linear repetitive processes (LRPs) are crucial in applications requiring high-precision, repetitive tasks.
    • Controlling LRPs over networks faces challenges due to limited bandwidth and data rate constraints.
    • Existing methods often use complex scheduling protocols to manage network resources.

    Purpose of the Study:

    • To develop an observer-based bounded H-infinity control strategy for shift-varying LRPs over networks with constrained bit rates.
    • To optimize bandwidth utilization by introducing a bit rate constraint model and an encoding-decoding mechanism.
    • To ensure bounded H-infinity performance within a finite horizon for networked LRPs.

    Main Methods:

    • Transforming the shift-varying LRP into a shift-varying two-dimensional (2-D) Fornasini-Marchesini model.
    • Proposing sufficient conditions in recursive linear matrix inequalities (LMIs) for bounded H-infinity performance.
    • Developing a component-based bit rate allocation strategy to expand the quantization region.

    Main Results:

    • Sufficient conditions derived using LMIs guarantee bounded H-infinity performance for the closed-loop system.
    • The proposed encoding-decoding mechanism effectively manages data transmission under bit rate constraints.
    • The component-based bit rate allocation strategy enhances quantization capabilities.

    Conclusions:

    • The developed observer-based bounded H-infinity control is effective for networked LRPs with bit rate constraints.
    • The method offers improved bandwidth efficiency compared to traditional scheduling protocols.
    • The approach is validated through a simulation example, demonstrating its practical applicability.