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

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

74
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...
74
PI Controller: Design01:24

PI Controller: Design

151
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
151
PD Controller: Design01:26

PD Controller: Design

153
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,...
153
Load-frequency control01:28

Load-frequency control

96
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
96
Controller Configurations01:22

Controller Configurations

73
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...
73
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

30
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
30

You might also read

Related Articles

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

Sort by
Same author

Real-time monitoring of bio-interface assembly enables high-sensitivity glucose sensing via no-core fiber with biocompatible composite coating.

Optics letters·2026
Same author

Preoperative machine learning algorithm for predicting urosepsis after percutaneous nephrolithotomy using EMR data.

Urolithiasis·2025
Same author

Probing the Growth Kinetics of Bioinspired Phenolic Nanocoating via Evanescent Wave Excited by Fiber-Optic Modal Interferometry.

Analytical chemistry·2025
Same author

Transient hydraulic pressure sensor based on single-hole-dual-core fiber Bragg grating.

Optics express·2025
Same author

Laser spectroscopy applied in radiocarbon dating with the bomb peak.

Optics express·2025
Same author

Spectral encoding based on narrowband/broadband modulations of QBIC for computational spectral imaging.

Optics express·2025
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

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

CAFF-CIL: Causality-Aware Freedom Forgetting Approach for Class-Incremental Learning.

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

Harmonic Autoencoding Framework for Multiple Tasks in Magnetic Particle Imaging Reconstruction.

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

A Survey on Human-Centric Voice-Face Multimodal Learning.

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

Vision-Assisted Foundation Model for Solving Multitask Vehicle Routing Problems.

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

FP3O: Enabling Proximal Policy Optimization in Multiagent Cooperation With Parameter-Sharing Versatility.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: May 14, 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

4.9K

Online Adaptive Optimal Control Algorithm Based on Weighted Policy Iteration.

Wanlin Tan, Rui Luo, Zhinan Peng

    IEEE Transactions on Neural Networks and Learning Systems
    |May 9, 2025
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new online learning algorithm for optimal control of nonlinear systems using weighted policy iteration (WPI). This method improves computational efficiency and simplifies conditions for convergence to optimal control policies.

    More Related Videos

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
    11:53

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

    Published on: December 9, 2012

    12.9K
    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

    1.5K

    Related Experiment Videos

    Last Updated: May 14, 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

    4.9K
    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
    11:53

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

    Published on: December 9, 2012

    12.9K
    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

    1.5K

    Area of Science:

    • * Control Theory
    • * Machine Learning
    • * Nonlinear Systems

    Background:

    • * Optimal control problems for nonlinear systems are challenging due to system complexity and approximation errors.
    • * Existing methods often require large neural networks (NNs) and strict persistently excited (PE) conditions.

    Purpose of the Study:

    • * To develop a novel online learning algorithm for optimal control of nonlinear systems.
    • * To address the impact of neural network approximation errors on control policy admissibility.
    • * To improve computational efficiency and relax existing conditions for convergence.

    Main Methods:

    • * Weighted Policy Iteration (WPI) algorithm.
    • * Integration of Neural Network (NN) approximation and experience replay techniques.
    • * Development of a relaxed persistently excited (PE) condition.

    Main Results:

    • * The proposed WPI-based algorithm converges uniformly to the optimal solution.
    • * Reduced number of neurons in the hidden layer leads to significant computational improvements.
    • * A relaxed PE condition is sufficient, easing practical implementation.

    Conclusions:

    • * The novel WPI algorithm effectively solves optimal control problems for nonlinear systems.
    • * The method offers enhanced computational efficiency and relaxed convergence conditions.
    • * Numerical experiments validate the proposed algorithm's effectiveness.