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

Measuring Acceleration Due to Gravity01:12

Measuring Acceleration Due to Gravity

603
Consider a coffee mug hanging on a hook in a pantry. If the mug gets knocked, it oscillates back and forth like a pendulum until the oscillations die out.
A simple pendulum can be described as a point mass and a string. Meanwhile, a physical pendulum is any object whose oscillations are similar to a simple pendulum, but cannot be modeled as a point mass on a string because its mass is distributed over a larger area. The behavior of a physical pendulum can be modeled using the principles of...
603
Differential Leveling01:12

Differential Leveling

236
Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
236
PID Controller01:19

PID Controller

174
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...
174
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

153
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...
153
PD Controller: Design01:26

PD Controller: Design

304
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,...
304
PI Controller: Design01:24

PI Controller: Design

388
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...
388

You might also read

Related Articles

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

Sort by
Same author

Amino acid metabolic reprogramming in immunotherapy for hepatocellular carcinoma: Adaptive resistance, patient stratification, and longitudinal monitoring.

Critical reviews in oncology/hematology·2026
Same author

Correction to Rapid Substrate Neutralization via Side-Chain Hydroxylated Copolymers for Efficient Vertical Alignment of Block Copolymers.

ACS macro letters·2026
Same author

Spin torque nano-oscillators with tilted magnetic anisotropy.

Nanoscale horizons·2026
Same author

Evolutionary differentiation of duplicated hoxb5 paralogs orchestrates calcium signaling and contractility.

Journal of molecular and cellular cardiology·2026
Same author

Rapid Substrate Neutralization via Side-Chain Hydroxylated Copolymers for Efficient Vertical Alignment of Block Copolymers.

ACS macro letters·2026
Same author

Multi-Sensor Collaborative Positioning in Range-Only Single-Beacon Systems: A Differential Chan-Gauss-Newton Algorithm with Sequential Data Fusion.

Sensors (Basel, Switzerland)·2025

Related Experiment Video

Updated: Aug 5, 2025

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

8.7K

An Improved Differential Evolution Adaptive Fuzzy PID Control Method for Gravity Measurement Stable Platform.

Xin Chen1, Hongwei Bian1, Hongyang He1

  • 1School of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China.

Sensors (Basel, Switzerland)
|March 30, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an improved differential evolution adaptive fuzzy PID control (IDEAFC) algorithm to enhance gravimeter stabilization accuracy. The IDEAFC algorithm significantly outperforms traditional methods in stabilizing platforms against disturbances.

Keywords:
PID controladaptive controlgravity measurementstable platform

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

1.7K
Method to Measure Tone of Axial and Proximal Muscle
10:41

Method to Measure Tone of Axial and Proximal Muscle

Published on: December 14, 2011

17.6K

Related Experiment Videos

Last Updated: Aug 5, 2025

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

8.7K
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

1.7K
Method to Measure Tone of Axial and Proximal Muscle
10:41

Method to Measure Tone of Axial and Proximal Muscle

Published on: December 14, 2011

17.6K

Area of Science:

  • Geophysics
  • Control Engineering

Background:

  • Platform gravimeters require high stabilization accuracy for precise gravity measurements.
  • System uncertainties like friction and nonlinear disturbances degrade stabilization performance.
  • Existing control methods struggle with the dynamic, nonlinear characteristics of stabilization platforms.

Purpose of the Study:

  • To develop an advanced control algorithm for improving gravimetric stabilization platform accuracy.
  • To address the impact of system uncertainties and nonlinear disturbances on control performance.
  • To achieve precise online adjustments of control parameters for enhanced stabilization.

Main Methods:

  • An improved differential evolution adaptive fuzzy PID control (IDEAFC) algorithm was developed.
  • Differential evolution optimizes initial parameters for the adaptive fuzzy PID controller.
  • The algorithm enables online parameter adjustments to counteract disturbances and state changes.

Main Results:

  • Simulation tests demonstrated the IDEAFC algorithm's effectiveness.
  • Static and swaying experiments confirmed superior stabilization accuracy.
  • On-board and shipboard experiments validated the algorithm's real-world applicability and performance.

Conclusions:

  • The IDEAFC algorithm significantly enhances stabilization accuracy compared to conventional PID and fuzzy control.
  • The proposed method offers a superior, available, and effective solution for platform gravimeter control.
  • Accurate online parameter adjustment is key to achieving high stabilization precision in dynamic environments.