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相关概念视频

Feedback control systems01:26

Feedback control systems

296
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...
296
Linear time-invariant Systems01:23

Linear time-invariant Systems

232
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
232
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

373
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....
373
Classification of Systems-II01:31

Classification of Systems-II

137
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
137
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

88
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
88
Transient and Steady-state Response01:24

Transient and Steady-state Response

164
In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
164

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相关实验视频

Updated: Jun 15, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

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Published on: September 8, 2023

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在不规则的间歇性DoS攻击下,适应性安全控制仅用于量子化非线性系统的输出.

Zhen Gao, Yongduan Song, Marios M Polycarpou

    IEEE transactions on cybernetics
    |August 26, 2024
    PubMed
    概括
    此摘要是机器生成的。

    本研究提出了一种新的适应性控制方法,用于面临量子化信号,不确定性和拒绝服务 (DoS) 攻击的非线性系统. 该方法确保了系统的稳定性,并尽量减少错误,尽管信号不可用和量子化挑战.

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    Published on: September 8, 2023

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    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
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    科学领域:

    • 控制理论 控制理论
    • 非线性系统是非线性系统.
    • 网络安全 网络安全

    背景情况:

    • 量子化信号驱动的控制对于非线性系统至关重要.
    • 不匹配的不确定性和拒绝服务 (DoS) 攻击使控制设计复杂化.
    • 对输入/输出信号的攻击使得状态和输入无法访问,阻碍了传统的控制方法.

    研究的目的:

    • 为非线性系统在量子化信号,不确定性和DoS攻击下开发一种新的自适应输出反控制方法.
    • 为了应对不可访问状态和量化,不可区分的输出信号所带来的挑战.
    • 确保闭环系统的稳定性和边界误差.

    主要方法:

    • 增益切换量子观察器的设计,用于状态估计.
    • 应用一级动态过来处理信号量化无差异性.
    • 开发用于未知量子化参数的自适应估计器,使用部门量子化器.
    • 建立控制器参数设计条件.

    主要成果:

    • 所有闭环信号都被证明是半球均最终边界 (SUUB).
    • 调节错误可以通过调整设计参数来最小化.
    • 拟议的方法有效地处理量化输出和间歇性DoS攻击.

    结论:

    • 新的自适应输出反控制方法成功地解决了量子化非线性系统中的复杂挑战.
    • 该方法提供了对不确定性和DoS攻击的强有力的控制.
    • 数字模拟验证了拟议方法的有效性和稳定性保证.