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 Frequency Domain01:26

Linear Approximation in Frequency Domain

502
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....
502
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.1K
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...
1.1K
Linear Differential Equations01:27

Linear Differential Equations

285
The integrating factor method provides a systematic way to solve first-order linear differential equations, especially those that cannot be handled by separation of variables. This method is particularly useful in modeling time-dependent physical systems influenced by both constant inputs and resistive forces. A common example is the motion of a car subjected to a constant engine force while experiencing air resistance proportional to its velocity.In such scenarios, Newton’s second law...
285
Feedback control systems01:26

Feedback control systems

800
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...
800
Separable Differential Equations01:20

Separable Differential Equations

365
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...
365
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

427
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
427

You might also read

Related Articles

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

Sort by
Same author

Spatial distribution of atmospheric PAHs and their genotoxicity in petrochemical industrialized Lanzhou valley, northwest China.

Environmental science and pollution research international·2017
Same author

Atmospheric removal of PM<sub>2.5</sub> by man-made Three Northern Regions Shelter Forest in Northern China estimated using satellite retrieved PM<sub>2.5</sub> concentration.

The Science of the total environment·2017
Same author

Structural formation and charge storage mechanisms for intercalated two-dimensional carbides MXenes.

Physical chemistry chemical physics : PCCP·2017
Same author

Three-dimensional porous ZnCo(2)O(4) sheet array coated with Ni(OH)(2) for high-performance asymmetric supercapacitor.

Journal of colloid and interface science·2017
Same author

Spatiotemporal expression of Wnt3a during striated muscle complex development in rat embryos with ethylenethiourea-induced anorectal malformations.

Molecular medicine reports·2017
Same author

Characterization of Schistosoma japonicum CP1412 protein as a novel member of the ribonuclease T2 molecule family with immune regulatory function.

Parasites & vectors·2017

Related Experiment Video

Updated: May 4, 2026

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

2.3K

Control design for one-sided Lipschitz nonlinear differential inclusions.

Xiushan Cai1, Hong Gao1, Leipo Liu2

  • 1College of Mathematics, Physics, and Information Engineering, Zhejiang Normal University, Jinhua 321004, China.

ISA Transactions
|January 7, 2014
PubMed
Summary
This summary is machine-generated.

This study presents a new control method for nonlinear differential inclusions (NDIs) with one-sided Lipschitz properties. The technique ensures system stabilization and accurate signal tracking for improved control system performance.

Keywords:
Exponential stabilizationLinear matrix inequalitiesNonlinear differential inclusionsOne-sided Lipschitz

More Related Videos

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

3.3K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

7.8K

Related Experiment Videos

Last Updated: May 4, 2026

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

2.3K
Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

3.3K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

7.8K

Area of Science:

  • Control Theory
  • Nonlinear Systems
  • Differential Inclusions

Background:

  • One-sided Lipschitz nonlinear differential inclusions (NDIs) present challenges in control design.
  • Stabilization and signal tracking are critical for closed-loop system performance.

Purpose of the Study:

  • To develop sufficient conditions for exponential stabilization of one-sided Lipschitz NDIs.
  • To extend the stabilization method for signal tracking control of these systems.

Main Methods:

  • Utilizing linear matrix inequality (LMI) theory for stabilization.
  • Designing a control law for asymptotic signal tracking.

Main Results:

  • Sufficient conditions for exponential stabilization are established.
  • A control law is designed to achieve asymptotic tracking of reference signals.
  • The effectiveness is demonstrated through two numerical examples.

Conclusions:

  • The proposed design technique effectively achieves stabilization and signal tracking for one-sided Lipschitz NDIs.
  • The LMI-based approach provides a robust framework for control design.