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

459
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...
459
PID Controller01:19

PID Controller

257
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...
257
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.1K
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...
1.1K
Neural Control of Respiration01:18

Neural Control of Respiration

3.0K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
3.0K
PD Controller: Design01:26

PD Controller: Design

368
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,...
368
Osmoregulation in Insects01:47

Osmoregulation in Insects

16.7K
Malpighian tubules are specialized structures found in the digestive systems of many arthropods, including most insects, that handle excretion and osmoregulation. The tubules are typically arranged in pairs and have a convoluted structure that increases their surface area.
16.7K

You might also read

Related Articles

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

Sort by
Same author

In Situ Ferroptosis with Global Dynamics Visualization for Glioblastoma Theranostics.

Journal of medicinal chemistry·2025
Same author

Correction: miR-377 induces senescence in human skin fibroblasts by targeting DNA methyltransferase 1.

Cell death & disease·2025
Same author

Hybrid Auricular Framework of Autologous Rib and Ear Cartilage for Microtia Reconstruction through a Preauricular Incision.

Plastic and reconstructive surgery·2025
Same author

En bloc resection for primary spinal tumors with huge intrathoracic involvement: a surgical intervention for neurological decompression and oncological control.

Frontiers in neurology·2025
Same author

Magnetic slippery microcatheter with artificial cilia for low-friction interventions.

Science advances·2025
Same author

A Mendelian randomization study between air pollutants and benign prostatic hyperplasia.

Medicine·2025
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: Sep 26, 2025

Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata
10:17

Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata

Published on: September 2, 2016

12.4K

Cyborg Moth Flight Control Based on Fuzzy Deep Learning.

Xiao Yang1, Xun-Lin Jiang2, Zheng-Lian Su3

  • 1School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China.

Micromachines
|April 23, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a noninvasive cyborg moth control method using ultraviolet (UV) rays and fuzzy deep learning. The approach achieves over 83% success in controlling moth flight parameters, outperforming existing methods.

Keywords:
cyborg mothdeep learningflight controlfuzzy systemsintelligent cyborgs

More Related Videos

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.8K
Early Metamorphic Insertion Technology for Insect Flight Behavior Monitoring
19:14

Early Metamorphic Insertion Technology for Insect Flight Behavior Monitoring

Published on: July 12, 2014

14.7K

Related Experiment Videos

Last Updated: Sep 26, 2025

Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata
10:17

Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata

Published on: September 2, 2016

12.4K
Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.8K
Early Metamorphic Insertion Technology for Insect Flight Behavior Monitoring
19:14

Early Metamorphic Insertion Technology for Insect Flight Behavior Monitoring

Published on: July 12, 2014

14.7K

Area of Science:

  • * Entomology
  • * Artificial Intelligence
  • * Control Systems Engineering

Background:

  • * Noninvasive cyborg insect control is challenging due to environmental uncertainties, limiting classical methods' accuracy.
  • * Existing noninvasive methods struggle with complex environments, necessitating advanced control strategies.
  • * Ultraviolet (UV) ray stimulation offers a noninvasive approach for insect control.

Purpose of the Study:

  • * To develop a noninvasive fuzzy deep learning method for cyborg moth flight control.
  • * To enhance control accuracy in complex and uncertain environments.
  • * To improve upon existing state-of-the-art cyborg insect control techniques.

Main Methods:

  • * A fuzzy deep learning framework comprising a Behavior Learner and a Control Learner.
  • * Hierarchical Behavior Learner for species, group, and individual behavior learning.
  • * Pythagorean fuzzy denoising autoencoder model for both learners.

Main Results:

  • * The proposed fuzzy deep learning method achieved a flight control success rate exceeding 83%.
  • * Demonstrated significant performance advantages over current state-of-the-art approaches.
  • * Successfully controlled cyborg moth flight parameters using noninvasive UV stimulation.

Conclusions:

  • * The noninvasive fuzzy deep learning approach offers a highly effective method for cyborg moth flight control.
  • * This technique shows promise for enhancing the precision and reliability of insect-robot systems.
  • * The study validates the potential of UV-stimulated cyborg insects for advanced applications.