Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

152
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
152
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

152
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
152
Linear time-invariant Systems01:23

Linear time-invariant Systems

202
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...
202
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

59
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
59
State Space Representation01:27

State Space Representation

160
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
160
First Order Systems01:21

First Order Systems

81
First-order systems, such as RC circuits, are foundational in understanding dynamic systems due to their straightforward input-output relationship. Analyzing their responses to different input functions under zero initial conditions reveals significant insights into system behavior.
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
81

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Dual-Modal Wearable PPG Smartwatch with AI-Enhanced Correction for High-Accuracy and Continuous AF Burden Assessment.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Metabolomics-guided discovery of previously undescribed lupane-type triterpenoids with anti-inflammatory activity from Mallotus repandus (Willd.) Müll. Arg.

Phytochemistry·2026
Same author

An Oligomeric Additive Bridges Inner and Outer Helmholtz Planes to Enable Reversible Zn Anodes via Spatial and Functional Decoupling.

Angewandte Chemie (International ed. in English)·2026
Same author

Design, Synthesis, and Biological Evaluation of Novel PAK1/HDAC10 Dual Inhibitors That Activate Antitumor Immunity for Triple-Negative Breast Cancer Treatment.

Journal of medicinal chemistry·2026
Same author

3D-Printed Ultra-Thin Solid Polymer Electrolytes with Superior Dielectric Properties for Wide Temperature Range All-Solid-State Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Ordered Polar Topological Domains Enabling Giant Second-Harmonic Generation in Ferroelectric Nematic Liquid Crystals.

Advanced materials (Deerfield Beach, Fla.)·2026

Related Experiment Video

Updated: May 24, 2025

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

13.7K

Evolutionary Fractional-Order Extended Kalman Filter of Cyber-Physical Power Systems.

Kang-Di Lu, Le Zhou, Zheng-Guang Wu

    IEEE Transactions on Cybernetics
    |March 3, 2025
    PubMed
    Summary

    This study introduces an enhanced fractional-order extended Kalman filter (EFOEKF) for cyber-physical power systems. The novel method improves state estimation accuracy, outperforming traditional filters in simulations.

    More Related Videos

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
    12:03

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

    Published on: May 25, 2019

    8.4K
    Interactive and Visualized Online Experimentation System for Engineering Education and Research
    08:35

    Interactive and Visualized Online Experimentation System for Engineering Education and Research

    Published on: November 24, 2021

    2.4K

    Related Experiment Videos

    Last Updated: May 24, 2025

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
    10:51

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

    Published on: March 10, 2011

    13.7K
    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
    12:03

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

    Published on: May 25, 2019

    8.4K
    Interactive and Visualized Online Experimentation System for Engineering Education and Research
    08:35

    Interactive and Visualized Online Experimentation System for Engineering Education and Research

    Published on: November 24, 2021

    2.4K

    Area of Science:

    • Electrical Engineering
    • Control Systems
    • Applied Mathematics

    Background:

    • State estimation is crucial for cyber-physical power systems (CPPSs) optimization, control, and security.
    • Fractional differential calculus offers more accurate modeling of physical phenomena than traditional integer calculus.
    • Existing methods face challenges in determining fractional orders and handling estimation difficulties in fractional-order systems.

    Purpose of the Study:

    • To propose a novel fractional-order extended Kalman filter (FOEKF) for CPPS state estimation.
    • To develop an evolutionary FOEKF (EFOEKF) by integrating genetic algorithms and deep ensemble learning for parameter optimization.
    • To enhance the EFOEKF for improved performance under adverse conditions like cyber-attacks.

    Main Methods:

    • Modeling the power system using fractional differential calculus for enhanced physical phenomenon description.
    • Employing deep ensemble learning to design the fitness function and a genetic algorithm for optimizing fractional orders.
    • Presenting the EFOEKF as an estimator for the fractional-order power system.
    • Developing an enhanced EFOEKF with an adapted exponential weighting function to address bad data scenarios.

    Main Results:

    • The proposed EFOEKF demonstrates superior performance compared to the standard Extended Kalman Filter (EKF) and the basic FOEKF.
    • The enhanced EFOEKF shows improved accuracy in state estimation, particularly under scenarios with bad data.
    • Evaluations on four different IEEE bus systems confirm the effectiveness of the proposed methods.

    Conclusions:

    • The novel EFOEKF, optimized using evolutionary and deep learning techniques, provides a robust solution for state estimation in fractional-order CPPSs.
    • The enhanced EFOEKF effectively mitigates the impact of bad data, enhancing system reliability.
    • The proposed approach offers significant improvements in mean absolute error for CPPS state estimation.