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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.
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State Space Representation01:27

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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...
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Separable Differential Equations01:20

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A separable differential equation is a type of first-order differential equation where the derivative dy/dx can be expressed as a product of two functions: one that depends only on x and another that depends only on y. This allows for the rearrangement of the equation so that all terms involving y are on one side, and all terms involving x are on the other. This process, known as the separation of variables, simplifies the process of solving the equation by enabling the integration of both...
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Linear Approximation in Time Domain01:21

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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.
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Transfer Function to State Space01:23

Transfer Function to State Space

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State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
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Differential Equations: Problem Solving01:21

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When analyzing the motion of falling objects, it is essential to consider not only the force of gravity but also the opposing force of air resistance. A practical example involves releasing a heavy test weight during a safety check on a ship. As the weight falls from rest, gravity accelerates it downward while air resistance exerts an upward force that increases with velocity. This dynamic interplay of forces is well described by differential equations, which provide a mathematical framework...
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Related Experiment Video

Updated: Feb 17, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
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Local bifurcations in differential equations with state-dependent delay.

Jan Sieber1

  • 1EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter EX4 4QJ, United Kingdom.

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|December 3, 2017
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Summary
This summary is machine-generated.

This study extends normal form analysis for dynamical systems to state-dependent delay differential equations (sd-DDEs). It confirms that predicted invariant manifolds with normal hyperbolicity persist in full sd-DDE models.

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Area of Science:

  • Dynamical Systems Analysis
  • Bifurcation Theory
  • Numerical Analysis

Background:

  • Normal form analysis is crucial for understanding local bifurcations of equilibria in dynamical systems.
  • Existing algorithms in DDE-Biftool handle constant delay differential equations (DDEs).
  • Extending these methods to state-dependent delay differential equations (sd-DDEs) presents unique challenges.

Purpose of the Study:

  • To extend existing normal form algorithms for constant delay differential equations to handle state-dependent delays.
  • To investigate the persistence of phenomena predicted by truncated normal forms in the full sd-DDE system.
  • To provide theoretical justification for numerical bifurcation studies involving sd-DDEs.

Main Methods:

  • Building upon established normal form algorithms for DDEs.
  • Developing extensions for systems with state-dependent delays.
  • Providing a partial argument for the persistence of invariant manifolds in sd-DDEs.

Main Results:

  • Successfully extended normal form computation methods to sd-DDEs.
  • Demonstrated that invariant manifolds with sufficient normal hyperbolicity, predicted by the normal form, exist in the full sd-DDE.
  • Addressed the challenge of higher regularity for local center manifolds in sd-DDEs.

Conclusions:

  • The developed methods enable the analysis of normal forms for sd-DDEs.
  • The findings support the validity of using truncated normal forms to predict behavior in sd-DDEs.
  • This work advances the computational tools for studying complex dynamical systems with state-dependent delays.