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

537
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...
537
Control System Problem01:21

Control System Problem

245
In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
245
Control Systems01:10

Control Systems

1.6K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.6K
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.2K
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...
1.2K
Root-Locus Method01:19

Root-Locus Method

264
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
264
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

177
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,...
177

You might also read

Related Articles

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

Sort by
Same author

Identification of a novel HIV-1 circulating recombinant form (CRF209_cpx) and its descendant unique recombinant form (URF) CRF209_cpx/B among MSM in Guangdong, southern China.

Virology journal·2026
Same author

CO<sub>2</sub> emission characteristics of hybrid electric vehicles in the tank-to-wheel (TTW) phase in plateau region.

Journal of environmental sciences (China)·2026
Same author

Flux Balance Analysis Reveals Potential Anti-HIV-1 Metabolic Targets.

Infectious diseases & immunity·2026
Same author

Pathogenic signatures and therapeutic evaluation of emergent MPXV Clade Ib in low-susceptibility and immunocompromised mouse models.

BMC microbiology·2026
Same author

Engraftment of sheep splenic lymphocytes into NBSGW mice and application in Brucella infection.

Animal models and experimental medicine·2026
Same author

Soft-event-triggered dynamic damping adaptive fuzzy constraints EPH control for robot manipulator.

ISA transactions·2026

Related Experiment Video

Updated: Nov 6, 2025

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.7K

Disturbance Observer-Based Feedback Linearization Control for a Quadruple-Tank Liquid Level System.

Xiangxiang Meng1, Haisheng Yu1, Jie Zhang1

  • 1College of Automation, Qingdao University, No. 308, Ningxia Road, Qing dao, China.

ISA Transactions
|May 11, 2021
PubMed
Summary
This summary is machine-generated.

A new control method using nonlinear disturbance observer (NDOB) improves liquid level control in quadruple-tank systems. This advanced feedback linearization technique outperforms traditional PID and sliding mode control methods.

Keywords:
Compensation controlFeedback linearizationLiquid level systemNDOBQuadruple-tank

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

1.9K
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

8.8K

Related Experiment Videos

Last Updated: Nov 6, 2025

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.7K
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

1.9K
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

8.8K

Area of Science:

  • Control Engineering
  • Process Control
  • Nonlinear Systems

Background:

  • Quadruple-tank liquid level (QTLL) systems exhibit complex nonlinear and coupled dynamics.
  • Accurate liquid level control is crucial for industrial process efficiency and stability.

Purpose of the Study:

  • To develop and validate a novel input/output feedback linearization control strategy for QTLL systems.
  • To enhance control performance by actively compensating for system uncertainties and disturbances.
  • To compare the proposed method against established control techniques like PID and DOBSMC.

Main Methods:

  • Mathematical modeling of the QTLL system using Bernoulli's law and mass conservation principles.
  • Design of an input/output feedback linearization controller tailored for the nonlinear QTLL dynamics.
  • Integration of a nonlinear disturbance observer (NDOB) for real-time disturbance estimation and compensation.
  • Simulation and experimental validation of the proposed control strategy.

Main Results:

  • The proposed NDOB-enhanced feedback linearization controller demonstrated superior performance in stabilizing liquid levels within the QTLL system.
  • The control strategy effectively estimated and compensated for system disturbances, leading to improved accuracy and robustness.
  • Comparative analysis showed significantly better control outcomes than conventional PID control and disturbance observer-based sliding mode control (DOBSMC).

Conclusions:

  • The novel NDOB-based input/output feedback linearization control offers a highly effective solution for managing complex QTLL systems.
  • This approach provides enhanced robustness and precision compared to existing control methods.
  • The findings support the adoption of this advanced control strategy in relevant industrial applications.