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

367
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...
367
Control Systems01:10

Control Systems

1.2K
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...
1.2K
Open and closed-loop control systems01:17

Open and closed-loop control systems

866
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...
866
Control Systems: Applications01:25

Control Systems: Applications

679
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
679
PD Controller: Design01:26

PD Controller: Design

310
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,...
310
PI Controller: Design01:24

PI Controller: Design

396
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...
396

You might also read

Related Articles

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

Sort by
Same author

Extremely Rare Complications in Uniportal Spinal Endoscopy: A Systematic Review with Unique Case Analyses.

Journal of clinical medicine·2024
Same author

Examination of Transmission Zeros in the MIMO Sensor-Based Propagation Environment Using a New Geometric Procedure.

Sensors (Basel, Switzerland)·2024
Same author

Outpatient Spine Procedures in Poland: Clinical Outcomes, Safety, Complications, and Technical Insights into an Ambulatory Spine Surgery Center.

Healthcare (Basel, Switzerland)·2023
Same author

Outpatient Spine Surgery in Poland: A Survey on Popularity, Challenges, and Future Perspectives.

Risk management and healthcare policy·2023
Same author

Autonomous x-ray scattering.

Nanotechnology·2023
Same author

A Measurement-Aided Control System for Stabilization of the Real-Life Stewart Platform.

Sensors (Basel, Switzerland)·2022

Related Experiment Video

Updated: Aug 8, 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

A Sensor-Aided System for Physical Perfect Control Applications in the Continuous-Time Domain.

Paweł Majewski1, Wojciech P Hunek1, Dawid Pawuś1

  • 1Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, Poland.

Sensors (Basel, Switzerland)
|February 28, 2023
PubMed
Summary

A new perfect control algorithm significantly enhances speed and accuracy while reducing energy consumption in industrial processes. This innovative approach outperforms existing methods like Linear Quadratic Regulator (LQR) control.

Keywords:
continuous-time systemsperfect controlpractical implementationreal-life plantstate-space description

More Related Videos

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.5K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K

Related Experiment Videos

Last Updated: Aug 8, 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
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.5K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K

Area of Science:

  • Control Engineering
  • Systems Science
  • Applied Mathematics

Background:

  • Continuous-time perfect control offers high speed and accuracy but suffers from excessive energy consumption.
  • Existing inverse model control strategies face limitations in industrial applications due to high energy demands.

Purpose of the Study:

  • To introduce an innovative perfect control scheme for multivariable real-life objects.
  • To address the energy consumption drawback of previous control algorithms.
  • To develop a sensor-aided approach for real-time engineering tasks requiring high precision.

Main Methods:

  • Development of a novel Inverse Model Control (IMC)-related approach.
  • Integration with a sensor-aided system for real-time implementation.
  • Comparative analysis against classical control laws, specifically Linear Quadratic Regulator (LQR).

Main Results:

  • The proposed IMC-based algorithm demonstrates superior performance compared to LQR.
  • Significant improvements observed in performance indices such as Integral Squared Error (ISE), Rise Time (RT), and Magnitude Overshoot (MOE).
  • Example: For a multi-tank system, the proposed method achieved ISE of 1.638, RT of 1.58×10^2, and MOE of 1.514×10^-7, outperforming LQR.

Conclusions:

  • The new perfect control algorithm presents a viable solution for energy-efficient, high-precision control in industrial applications.
  • The sensor-aided IMC approach shows substantial implementation potential for real-time engineering tasks.
  • The developed method offers a significant advancement over traditional control strategies like LQR.