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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...
516
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

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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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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Feedback control systems01:26

Feedback control systems

475
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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Classification of Systems-II01:31

Classification of Systems-II

254
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,
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Second Order systems II01:18

Second Order systems II

201
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
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Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements.

Liheng Chen, Yanzheng Zhu, Choon Ki Ahn

    IEEE Transactions on Neural Networks and Learning Systems
    |December 10, 2021
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    Summary

    This study introduces a novel neural network (NN) observer for switched systems using quantized data. The method accurately estimates states and actuator efficiency, even with degraded actuators, using persistent dwell-time switching.

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    Area of Science:

    • Control Systems Engineering
    • Artificial Intelligence
    • Nonlinear Systems

    Background:

    • Adaptive observers are crucial for estimating system states and parameters.
    • Quantized output signals present challenges in observer design due to information loss.
    • Switched systems require specialized observer designs that account for system mode transitions.

    Purpose of the Study:

    • To design a novel adaptive neural network (NN) observer for continuous-time switched systems with quantized output signals.
    • To incorporate persistent dwell-time (PDT) switching to unify fast and slow switching behaviors.
    • To achieve accurate state and actuator efficiency factor estimation despite actuator degradation.

    Main Methods:

    • Development of a novel NN observer with adaptive laws based on quantized measurements.
    • Application of persistent dwell-time (PDT) switching for robust observer design.
    • Validation through simulation examples to demonstrate estimation accuracy.

    Main Results:

    • The proposed NN observer effectively estimates system states and actuator efficiency factors.
    • The observer demonstrates robustness against actuator degradation.
    • The PDT switching strategy unifies different switching speeds within the observer design.

    Conclusions:

    • The developed NN observer design is effective for continuous-time switched systems with quantized outputs.
    • The approach provides accurate state and actuator efficiency estimation under challenging conditions.
    • The use of PDT switching enhances the observer's applicability to diverse switching scenarios.