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

307
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...
307
Controller Configurations01:22

Controller Configurations

94
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...
94
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

95
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...
95
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

81
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,...
81
PD Controller: Design01:26

PD Controller: Design

222
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
222
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

89
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....
89

You might also read

Related Articles

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

Sort by
Same author

Approximate Optimal Control for Morphing Aircraft via Attention Meta-Learning and Continual Learning.

IEEE transactions on neural networks and learning systems·2026
Same author

Recent Advances on Off-Policy Reinforcement Learning for Optimization Control.

IEEE transactions on cybernetics·2026
Same author

Output Synchronization via Intermittent Dynamic Event-Triggered Sampled-Data Security Control for Delayed Reaction--Diffusion Neural Networks.

IEEE transactions on cybernetics·2026
Same author

A Dynamic Neural Network-Based Control Method Using Reinforcement Learning for Nonlinear Parameter-Varying System With Application to Morphing Aircraft.

IEEE transactions on neural networks and learning systems·2025
Same author

Human Behavior Identification for Linear Systems in Adversarial Environments by Adaptive Inverse Reinforcement Learning.

IEEE transactions on cybernetics·2025
Same author

Boundary Sampled-Data Synchronization of Delayed Reaction-Diffusion Neural Networks.

IEEE transactions on cybernetics·2025
Same journal

A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths.

IEEE transactions on cybernetics·2026
Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026
Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026
Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026
Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Jun 26, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.0K

Adaptive Inverse Nonlinear Optimal Control Based on Finite-Time Concurrent Learning and Semidefinite Programming.

Huai-Ning Wu, Jie Lin

    IEEE Transactions on Cybernetics
    |May 13, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study presents an adaptive inverse optimal control (IOC) method for nonlinear affine systems. It recovers cost functionals using system states, integrating finite-time concurrent learning (FTCL) and semidefinite programming (SDP) without needing persistent excitation.

    More Related Videos

    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

    1.6K
    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.4K

    Related Experiment Videos

    Last Updated: Jun 26, 2025

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    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

    1.6K
    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.4K

    Area of Science:

    • Control Theory
    • Machine Learning
    • Nonlinear Systems

    Background:

    • Inverse Optimal Control (IOC) is crucial for understanding system behavior.
    • Traditional methods often require persistent excitation (PE), limiting applicability.
    • Nonlinear affine systems present unique control challenges.

    Purpose of the Study:

    • To develop an adaptive IOC approach for nonlinear affine systems.
    • To recover the cost functional using only system state data.
    • To eliminate the need for persistent excitation (PE) in IOC.

    Main Methods:

    • Integration of finite-time concurrent learning (FTCL) and semidefinite programming (SDP).
    • Utilizing an identifier neural network (NN) to approximate nonlinear control policies.
    • Employing a value NN to approximate the value function for SDP formulation.

    Main Results:

    • An FTCL-based update law for online estimation of NN weights.
    • Analysis of finite-time convergence and uniformly ultimately boundedness (UUB) of estimation errors.
    • Successful determination of cost functional weighting matrices via SDP.

    Conclusions:

    • The proposed adaptive IOC method effectively recovers cost functionals for nonlinear affine systems.
    • The integration of FTCL and SDP overcomes traditional limitations like PE.
    • Simulation results validate the efficacy of the novel approach.