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

Feedback control systems01:26

Feedback control systems

789
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...
789
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

394
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,...
394
Controller Configurations01:22

Controller Configurations

427
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
427
State Space Representation01:27

State Space Representation

692
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...
692
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

424
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....
424
Classification of Systems-I01:26

Classification of Systems-I

652
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
652

You might also read

Related Articles

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

Sort by
Same author

Variance-constrained multi-view ensemble broad network for imbalanced data.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Learning to Super-Resolve Face Images via Dual-Domain Multi-scale Feature Interaction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Effectiveness of heterologous mRNA vaccine boosters during an Omicron wave of COVID-19: a cross-sectional study in Macao (China).

Journal of thoracic disease·2026
Same author

Fast BCIs: Leveraging Dual-Scale Time Windows with Test-Time Adaptation to Enhance Accuracy.

IEEE transactions on bio-medical engineering·2026
Same author

Riemannian Acceleration for Sparse PCA With Separable Structure and Second-Order Information Exploration.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Hierarchical memory-based deep reinforcement learning in simulated survival environments.

Neural networks : the official journal of the International Neural Network Society·2026

Related Experiment Video

Updated: Mar 24, 2026

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

2.2K

Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints.

Yan-Jun Liu, Jing Li, Shaocheng Tong

    IEEE Transactions on Neural Networks and Learning Systems
    |March 16, 2016
    PubMed
    Summary

    This study introduces an adaptive neural network control method using a barrier Lyapunov function (BLF) to stabilize uncertain nonlinear systems with full-state constraints. The approach ensures constraints are not violated, leading to bounded system signals and accurate output tracking.

    Related Experiment Videos

    Last Updated: Mar 24, 2026

    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

    2.2K

    Area of Science:

    • Control Theory
    • Nonlinear Systems
    • Artificial Intelligence

    Background:

    • State constraints are common in real-world systems and their violation must be avoided.
    • Stabilizing uncertain nonlinear systems with strict constraints is a significant challenge in control engineering.

    Purpose of the Study:

    • To develop an adaptive neural network control method for stabilizing uncertain nonlinear strict-feedback systems with full-state constraints.
    • To ensure that state constraints are never violated during system operation.

    Main Methods:

    • Utilizing a barrier Lyapunov function (BLF) within a backstepping design framework.
    • Employing minimal learning parameters in the BLF backstepping design.
    • Applying Lyapunov analysis to prove system stability and performance.

    Main Results:

    • The proposed method successfully prevents the violation of full-state constraints.
    • All signals within the closed-loop system are proven to be semiglobal uniformly ultimately bounded.
    • The system output effectively tracks the desired trajectory.

    Conclusions:

    • The adaptive neural network control method with BLF is effective for stabilizing uncertain nonlinear systems under full-state constraints.
    • The developed technique offers a robust solution for practical control problems where state constraints are critical.