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

Open and closed-loop control systems01:17

Open and closed-loop control systems

1.5K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.5K
PI Controller: Design01:24

PI Controller: Design

1.1K
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...
1.1K
PID Controller01:19

PID Controller

623
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
623
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

761
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
761
Controller Configurations01:22

Controller Configurations

330
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...
330
Feedback control systems01:26

Feedback control systems

657
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...
657

You might also read

Related Articles

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

Sort by
Same author

Integrated Control Strategies for a Precision Long-Travel Stage: Applications in Micro-Lens Fabrication.

Micromachines·2025
Same author

Assessment of Gait and Balance in Elderly Individuals with Knee Osteoarthritis Using Inertial Measurement Units.

Sensors (Basel, Switzerland)·2025
Same author

Clinical Trials of a Stroke Rehabilitation Trainer Employing a Speed-Adapted Treadmill.

Sensors (Basel, Switzerland)·2025
Same author

Strategic Design of Biocompatible, Glistening-Free, and Foldable Artificial Intraocular Lenses Based on Hydro-Amphiphilic Ternary Copolymers.

Biomacromolecules·2025
Same author

Age-Related Influence on Static and Dynamic Balance Abilities: An Inertial Measurement Unit-Based Evaluation.

Sensors (Basel, Switzerland)·2024
Same author

Human Posture Transition-Time Detection Based upon Inertial Measurement Unit and Long Short-Term Memory Neural Networks.

Biomimetics (Basel, Switzerland)·2023
Same journal

Correction: Kang et al. Fluid Flow to Electricity: Capturing Flow-Induced Vibrations with Micro-Electromechanical-System-Based Piezoelectric Energy Harvester. <i>Micromachines</i> 2024, <i>15</i>, 581.

Micromachines·2026
Same journal

Femtosecond Laser Texturing of Wood Coatings with Bio-Based Epoxy and Wax Additives for Enhanced Hydrophobicity.

Micromachines·2026
Same journal

Engineering of Optoelectronic Devices for Renewable Energy Applications.

Micromachines·2026
Same journal

Phase Transformation and Electrochemical Behavior of Hexagonal TiO<sub>2</sub> Nanotubes Under Different Annealing Temperatures and Heating Rates.

Micromachines·2026
Same journal

Process Optimization and Predictive Modeling of Femtosecond Laser Precision Milling for Commercial PMMA Slices.

Micromachines·2026
Same journal

A Hybrid Preprocessing Multi-Objective Surrogate Model for Thermal MEMS Actuators.

Micromachines·2026
See all related articles

Related Experiment Video

Updated: Jan 7, 2026

Measurement of Extracellular Ion Fluxes Using the Ion-selective Self-referencing Microelectrode Technique
09:18

Measurement of Extracellular Ion Fluxes Using the Ion-selective Self-referencing Microelectrode Technique

Published on: May 3, 2015

14.4K

AI-Based Model Estimation for a Precision Positioning Stage Employing Multiple Control Switching.

Fu-Cheng Wang1, Bo-Xuan Zhong1, Chi-Wei Wen1

  • 1Department of Mechanical Engineering, National Taiwan University, Taipei 106319, Taiwan.

Micromachines
|December 31, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an AI framework for real-time piezoelectric transducer (PZT) model estimation. It enhances control performance by continuously updating system models with eXtreme Gradient Boosting (XGBoost), improving accuracy and adaptability.

Keywords:
PZTartificial intelligencecontrol switchingmodel estimationstage

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.1K
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

9.0K

Related Experiment Videos

Last Updated: Jan 7, 2026

Measurement of Extracellular Ion Fluxes Using the Ion-selective Self-referencing Microelectrode Technique
09:18

Measurement of Extracellular Ion Fluxes Using the Ion-selective Self-referencing Microelectrode Technique

Published on: May 3, 2015

14.4K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.1K
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

9.0K

Area of Science:

  • Control Systems Engineering
  • Artificial Intelligence
  • Materials Science

Background:

  • Conventional fixed controllers for piezoelectric transducer (PZT) stages exhibit trade-offs between response speed and smoothness.
  • Existing multi-controller switching mechanisms rely on nominal plant models, neglecting operational variations and limiting performance.
  • Accurate real-time system modeling is crucial for adaptive control in dynamic environments.

Purpose of the Study:

  • To develop a real-time model estimation framework for enhancing piezoelectric transducer (PZT) stage control.
  • To improve the performance of multi-controller switching mechanisms by incorporating adaptive model updates.
  • To address the limitations of conventional controllers and existing switching mechanisms that neglect system variations.

Main Methods:

  • Implementation of an artificial intelligence-based framework for real-time model estimation.
  • Utilization of the eXtreme Gradient Boosting (XGBoost) algorithm for continuous system model updating.
  • Integration of the real-time model estimator with a multi-controller switching mechanism for adaptive control.

Main Results:

  • The proposed XGBoost-based model estimator significantly improves prediction accuracy by continuously updating the system model.
  • Adaptive adjustment of controllers based on updated models enhances the overall performance of the switching mechanism.
  • Simulations and experiments validate the effectiveness of the real-time estimation and adaptive control approach.

Conclusions:

  • The developed real-time model estimation framework effectively enhances piezoelectric transducer (PZT) stage control performance.
  • XGBoost-based adaptive modeling provides a robust solution for systems with operational variations.
  • The integration of real-time estimation and adaptive control offers a promising direction for advanced control systems.