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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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Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
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Linear Approximation in Frequency Domain01:26

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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.
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Control System Problem01:21

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In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
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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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In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
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Updated: Dec 16, 2025

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An improved parametric model for hysteresis loop approximation.

Rostislav V Lapshin1

  • 1Solid Nanotechnology Laboratory, Institute of Physical Problems, Zelenograd, Moscow 124460, Russian Federation.

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Summary

This study introduces an improved analytical model for hysteresis loops, significantly reducing approximation errors to under 1%. The enhanced model accurately simulates various hysteresis loop types, proving useful for scientific instrument simulations.

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Area of Science:

  • Physics
  • Materials Science
  • Analytical Modeling

Background:

  • Hysteresis loops are crucial in physical measurements, but existing analytical models have limitations in accuracy and flexibility.
  • Accurate modeling of hysteresis is essential for understanding and simulating the behavior of various physical systems and instruments.

Purpose of the Study:

  • To enhance an existing analytical model for hysteresis loops by incorporating additional parameters.
  • To improve the accuracy and versatility of hysteresis loop approximation for rate-independent symmetrical loops.
  • To demonstrate the model's applicability in simulating scientific instruments with hysteresis elements.

Main Methods:

  • Inclusion of three phase shifts into the parametric hysteresis loop model.
  • Development of smooth transitions for loop tilting and curvature adjustment.
  • Validation of the model against various known hysteresis loop types.

Main Results:

  • The improved model achieves an approximation error not exceeding 1%, a significant reduction compared to existing models.
  • The model successfully approximates a wide range of rate-independent symmetrical hysteresis loops.
  • Demonstrated capability to generate diverse loop types including piecewise-linear, hybrid, and inverse loops.

Conclusions:

  • The enhanced analytical model offers superior accuracy and flexibility for approximating hysteresis loops.
  • This improved model is valuable for the simulation of scientific instruments, such as probe microscope piezoscanners.
  • The model provides a robust tool for researchers dealing with hysteresis phenomena in physical measurements.