Jove
Visualize
Contact Us

Related Concept Videos

Multimachine Stability01:25

Multimachine Stability

218
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
218
Feedback control systems01:26

Feedback control systems

392
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...
392
Effects of feedback01:24

Effects of feedback

675
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
675
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

144
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
144
Stability01:28

Stability

184
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
184
Control System Problem01:21

Control System Problem

166
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.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
166

You might also read

Related Articles

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

Sort by
Same author

Exact computation of Lyapunov exponents via system parameters in multi-triangle chaotic maps: Bifurcation analysis and circuit realization.

Chaos (Woodbury, N.Y.)·2026
Same author

Simple chemical systems with chaos.

Chaos (Woodbury, N.Y.)·2026
Same author

Reverse Newhouse-Ruelle-Takens route to chaos and time-dependent Hamiltonian formulation of a generalized Muthuswamy-Chua system.

Chaos (Woodbury, N.Y.)·2026
Same author

Analyzing the relationship between synchronization dynamics in hypernetworks and their single-interaction counterparts.

Chaos (Woodbury, N.Y.)·2025
Same author

The transition to synchronization of networked systems.

Nature communications·2024
Same author

Synchronization enhancement subjected to adaptive blinking coupling.

Chaos (Woodbury, N.Y.)·2024
Same journal

Multiscale dynamics of special memristive ion channels in a neural circuit.

Chaos (Woodbury, N.Y.)·2026
Same journal

Symmetry-protected delay spectroscopy in oscillator networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Mesoscale community organization governs epidemic onset and spread in metapopulations.

Chaos (Woodbury, N.Y.)·2026
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
See all related articles
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 Experiment Video

Updated: Aug 30, 2025

Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements
14:18

Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements

Published on: February 28, 2016

11.5K

Generalized multistability and its control in a laser.

Riccardo Meucci1, Jean Marc Ginoux2, Mahtab Mehrabbeik3

  • 1Istituto Nazionale di Ottica-CNR, Largo E. Fermi 6, 50125 Firenze, Italy.

Chaos (Woodbury, N.Y.)
|September 1, 2022
PubMed
Summary
This summary is machine-generated.

We explored a laser model with cavity loss modulation, finding that multistability depends on system dissipation. A secondary perturbation can eliminate bistability, favoring the less dissipative attractor, even when chaotic.

More Related Videos

Low-cost Custom Fabrication and Mode-locked Operation of an All-normal-dispersion Femtosecond Fiber Laser for Multiphoton Microscopy
08:48

Low-cost Custom Fabrication and Mode-locked Operation of an All-normal-dispersion Femtosecond Fiber Laser for Multiphoton Microscopy

Published on: November 22, 2019

7.7K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.1K

Related Experiment Videos

Last Updated: Aug 30, 2025

Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements
14:18

Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements

Published on: February 28, 2016

11.5K
Low-cost Custom Fabrication and Mode-locked Operation of an All-normal-dispersion Femtosecond Fiber Laser for Multiphoton Microscopy
08:48

Low-cost Custom Fabrication and Mode-locked Operation of an All-normal-dispersion Femtosecond Fiber Laser for Multiphoton Microscopy

Published on: November 22, 2019

7.7K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.1K

Area of Science:

  • Nonlinear Dynamics
  • Laser Physics
  • Chaos Theory

Background:

  • The laser model with cavity loss modulation, first studied in 1982, exhibits chaos and generalized multistability.
  • Multistability is defined as the coexistence of multiple attractors in nonlinear dynamical systems.
  • Previous research highlighted the complexity arising from simple nonlinear systems.

Purpose of the Study:

  • To investigate the dependence of multistability on system dissipation in the laser model.
  • To explore the control of bistability using a secondary sinusoidal perturbation.
  • To determine the conditions under which a specific attractor can be selected.

Main Methods:

  • Revisiting the established laser model with cavity loss modulation.
  • Analyzing the system's behavior under varying dissipation levels.
  • Applying a secondary sinusoidal perturbation with controlled relative phase.

Main Results:

  • Demonstrated that multistability in this laser model is directly influenced by system dissipation.
  • Showed that a secondary perturbation can successfully remove bistability.
  • Identified that the surviving attractor is consistently the one with lower dissipation, even when one attractor is chaotic.

Conclusions:

  • The dissipation level is a critical factor governing multistability in modulated laser systems.
  • A secondary perturbation offers an effective strategy to control and select attractors.
  • This control method is particularly valuable for suppressing chaotic attractors in favor of stable, less dissipative ones.