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

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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, the...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
State Space Representation01:27

State Space Representation

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...
Feedback control systems01:26

Feedback control systems

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...
Linear Circuits01:17

Linear Circuits

A linear circuit is characterized by its output having a direct proportionality to its input, adhering to the linearity property, which encompasses the principles of homogeneity (scaling) and additivity. Homogeneity dictates that when the input, also referred to as the excitation, is multiplied by a constant factor, the output, known as the response, is correspondingly scaled by the same constant factor. For instance, if the current is multiplied by a constant 'k,' the voltage likewise...
Effects of feedback01:24

Effects of feedback

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...

You might also read

Related Articles

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

Sort by
Same author

Protein Phosphatase 1 γ Modulates Steady-State BAD Phosphorylation and Murine Platelet Survival.

Thrombosis and haemostasis·2023
Same author

[A CASE REPORT OF FUNGUS BALL FOUND DURING TRANSURETHRAL URETEROLITHOTOMY].

Nihon Hinyokika Gakkai zasshi. The japanese journal of urology·2020
Same author

Direct Observation of Long-Chain Branches in a Low-Density Polyethylene.

Scientific reports·2019
Same author

Depth profiling of APTES self-assembled monolayers using surface-enhanced confocal Raman microspectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2017
Same author

[An Intravesical Foreign Body after Caesarean Section and Tissue Fixing System (TFS) Operation : Two Case Reports].

Hinyokika kiyo. Acta urologica Japonica·2016
Same author

[Case of a Plasmacytoid Urothelial Carcinoma Identified Due to the Hardening of the Abdominal Wall].

Hinyokika kiyo. Acta urologica Japonica·2016

Related Experiment Video

Updated: Jun 14, 2026

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

Non-Gaussian state generation from linear elements via feedback.

Masahiro Yanagisawa1

  • 1Department of Engineering, The Australian National University, Canberra ACT 0200, Australia.

Physical Review Letters
|April 7, 2010
PubMed
Summary

This study introduces a novel multiplicative feedback control for generating quantum non-Gaussian states using linear optics. This method enables deterministic creation of quantum superposition states, advancing quantum technology.

Related Experiment Videos

Last Updated: Jun 14, 2026

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

Area of Science:

  • Quantum Optics
  • Quantum Information Science

Background:

  • Traditional methods for generating quantum states often rely on additive control.
  • Deterministic generation of quantum superposition states remains a challenge in quantum optics.

Purpose of the Study:

  • To present a novel feedback scheme for producing quantum non-Gaussian states.
  • To enable the deterministic generation of quantum superposition states using linear optical elements.

Main Methods:

  • Implementation of a multiplicative feedback control strategy.
  • Utilizing quantum nondemolition measurement of a quadrature.
  • Employing a multifeedback structure and Lyapunov stability for control design.

Main Results:

  • Demonstration of a feedback scheme capable of producing quantum non-Gaussian states.
  • Successful deterministic generation of quantum superposition states.

Conclusions:

  • The proposed multiplicative feedback control offers an effective alternative to additive methods.
  • This scheme advances the capability for deterministic generation of crucial quantum states for quantum information processing.