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Related Concept Videos

Linear time-invariant Systems01:23

Linear time-invariant Systems

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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...
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Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

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Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
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Transfer Function in Control Systems01:21

Transfer Function in Control Systems

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

BIBO stability of continuous and discrete -time systems

466
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....
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Transient and Steady-state Response01:24

Transient and Steady-state Response

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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.
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Basic Continuous Time Signals01:22

Basic Continuous Time Signals

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Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
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Event-Triggered Multiasynchronous H∞ Control for Markov Jump Systems With Transmission Delay.

Pengyu Zeng, Feiqi Deng, Ze-Hao Wu

    IEEE Transactions on Cybernetics
    |April 5, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces multiple event-triggered schemes (ETSs) for Markov jump systems with transmission delays, reducing sampling frequency. A novel approach using a hidden Markov model (HMM) and packet loss schedule ensures H-infinity performance despite network delays.

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    Area of Science:

    • Control Systems Engineering
    • Stochastic Systems

    Background:

    • Markov jump systems are prone to asynchronous behavior and transmission delays.
    • Event-triggered schemes (ETSs) aim to reduce communication load by triggering control actions only when necessary.
    • Existing methods struggle with the combined challenges of multiasynchronous jumps, multiple ETSs, and network-induced transmission delays.

    Purpose of the Study:

    • To develop an event-triggered multiasynchronous H-infinity control strategy for Markov jump systems with transmission delay.
    • To reduce the sampling frequency of control systems through multiple ETSs.
    • To ensure robust H-infinity performance despite asynchronous jumps and network-induced delays.

    Main Methods:

    • Employing a hidden Markov model (HMM) to characterize multiasynchronous jumps across subsystems, ETSs, and controllers.
    • Constructing a time-delay closed-loop model based on the HMM.
    • Introducing a packet loss schedule to handle data disorder caused by large transmission delays.
    • Utilizing the Lyapunov-Krasovskii functional method for controller design and performance analysis.

    Main Results:

    • A unified time-delay closed-loop system model is established, accounting for packet loss.
    • Sufficient conditions for guaranteeing H-infinity performance are derived.
    • The proposed control strategy effectively manages multiasynchronous jumps and transmission delays.
    • Numerical examples validate the effectiveness of the developed control approach.

    Conclusions:

    • The proposed event-triggered control strategy effectively addresses H-infinity control for Markov jump systems with transmission delays and multiasynchronous jumps.
    • The integration of HMM and a packet loss schedule provides a robust framework for handling network uncertainties.
    • The method successfully reduces sampling frequency while maintaining desired system performance.