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

110
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,...
110
Stability01:28

Stability

167
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...
167
Linear time-invariant Systems01:23

Linear time-invariant Systems

302
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...
302
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

457
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
457
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

153
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
153
Feedback control systems01:26

Feedback control systems

356
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...
356

You might also read

Related Articles

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

Sort by
Same author

The optineurin fatty acid-binding protein 3 axis: A novel regulator of autophagy and apoptosis in myocardial infarction.

International journal of biological macromolecules·2026
Same author

Balancing energy resilience and mobility: a multi-objective strategy for deploying shared autonomous electric vehicles during power outages.

Npj sustainable mobility and transport·2026
Same author

Quercetin ameliorates ox-LDL-induced cellular senescence of aortic endothelial cells and macrophages by p16/p21, p53/SERPINE1, and AMPK/mTOR pathways.

European journal of medical research·2025
Same author

Changes of perioperative cognitive function and its effect on quality of life in laryngeal cancer.

Perioperative medicine (London, England)·2025
Same author

Highly multiplexed fluorescence microscopy with spectrally tunable semiconducting polymer dots.

Science advances·2024
Same author

SCGB1A1 as a novel biomarker and promising therapeutic target for the management of HNSCC.

Oncology letters·2024

Related Experiment Video

Updated: Jul 31, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K

Adaptive fixed-time stabilization for a class of nonlinear uncertain systems.

Yan Zhao1, Jianli Yao1, Jie Tian1

  • 1School of Science, Shandong Jianzhu University, Jinan 250101, China.

Mathematical Biosciences and Engineering : MBE
|May 10, 2023
PubMed
Summary

This study addresses adaptive fixed-time stabilization for nonlinear systems with uncertainties. The proposed control strategy ensures system states reach the origin in a fixed time, independent of initial conditions.

Keywords:
adaptive controlfinite-time controlfixed-time stabilizationparametric uncertainty

More Related Videos

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

8.7K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K

Related Experiment Videos

Last Updated: Jul 31, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K
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

8.7K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K

Area of Science:

  • Control Engineering
  • Nonlinear Systems Theory
  • Adaptive Control

Background:

  • Finite-time stability (FTS) is crucial in nonlinear control.
  • Fixed-time stability (FxTS) offers settling times independent of initial states.
  • Challenges include nonlinear parametric uncertainties and uncertain control coefficients.

Purpose of the Study:

  • Investigate adaptive fixed-time stabilization for nonlinear systems.
  • Develop a control strategy for systems with uncertainties.
  • Ensure fixed-time convergence and bounded signals.

Main Methods:

  • Adaptive estimation techniques.
  • Adding one power integrator (AOPI) design tool.
  • Two-phase control strategy.
  • Fixed-time Lyapunov stability theory.

Main Results:

  • Achieved fixed-time stabilization for nonlinear systems.
  • Ensured boundedness of all system signals.
  • Demonstrated efficacy via pendulum system simulations.

Conclusions:

  • The proposed adaptive fixed-time stabilizing control is effective.
  • The method handles nonlinear parametric uncertainties.
  • Validated by practical application to the pendulum system.