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

PD Controller: Design01:26

PD Controller: Design

664
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,...
664
PI Controller: Design01:24

PI Controller: Design

1.3K
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...
1.3K
Reinforcement Schedules01:24

Reinforcement Schedules

532
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
532
Reclosers and Fuses01:26

Reclosers and Fuses

486
Automatic circuit reclosers enhance the protection of distribution circuits by interrupting and auto-reclosing an AC circuit according to a preset sequence. They effectively manage temporary faults on overhead distribution lines, often caused by tree limbs or wildlife, by briefly disrupting service to improve overall reliability. However, contact with reclosers or energized broken conductors on the ground can pose serious hazards.
A comprehensive protection scheme for radial distribution...
486
Circuit Breaker and Fuse Selection01:23

Circuit Breaker and Fuse Selection

617
A circuit breaker is a device engineered to interrupt fault currents and sometimes reclose automatically. When a fault current is detected, the breaker separates the electrical contacts, which generates an arc. This arc is extinguished by methods such as elongation, cooling, or splitting, depending on the breaker's design. Breakers are categorized based on the voltage they operate at and the medium used for arc extinction, such as air, oil, SF6 gas, or vacuum.
In high-voltage systems,...
617
Group Design02:01

Group Design

10.8K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
10.8K

You might also read

Related Articles

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

Sort by
Same author

Machine learning investigation of marangoni convection in hybrid nanofluids with Darcy-Forchheimer.

Scientific reports·2025
Same author

Bifurcation phenomena in Taylor-Couette flow in a very short annulus with radial through-flow.

Scientific reports·2022
Same author

On the ridge of instability in ferrofluidic Couette flow via alternating magnetic field.

Scientific reports·2021
Same author

Effects of an imposed axial flow on a Ferrofluidic Taylor-Couette flow.

Scientific reports·2019
Same author

Transient behavior between multi-cell flow states in ferrofluidic Taylor-Couette flow.

Chaos (Woodbury, N.Y.)·2017
Same author

Dynamics of ferrofluidic flow in the Taylor-Couette system with a small aspect ratio.

Scientific reports·2017

Related Experiment Video

Updated: Feb 14, 2026

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
08:04

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

4.8K

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.

Sakthivel Manikandan Sundharam1, Nicolas Navet2, Sebastian Altmeyer3

  • 1Laboratory of Advanced Software Systems (LASSY), CSC Research Unit, University of Luxembourg, Maison du Nombre, L-4364 Esch-sur-Alzette, Luxembourg. sakthivel.sundharam@uni.lu.

Sensors (Basel, Switzerland)
|February 21, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a co-design framework using timing tolerance contracts to bridge gaps between control and real-time software engineering in Cyber-Physical Systems (CPS). It ensures functional and non-functional requirements are met through integrated design and verification steps.

Keywords:
co-simulationcontrol softwarecontrol system performancecontroller modelinput jittersinput-to-output delaymodel-driven engineeringoutput jittersreal-time schedulingschedulabilitystabilitytiming tolerance contractvarying execution-times

More Related Videos

Fused Filament Fabrication FFF of Metal-Ceramic Components
08:43

Fused Filament Fabrication FFF of Metal-Ceramic Components

Published on: January 11, 2019

18.1K
A Do-it-yourself System for Scheduled Feeding of Laboratory Rodents in Their Home Cage
04:49

A Do-it-yourself System for Scheduled Feeding of Laboratory Rodents in Their Home Cage

Published on: June 6, 2025

955

Related Experiment Videos

Last Updated: Feb 14, 2026

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
08:04

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

4.8K
Fused Filament Fabrication FFF of Metal-Ceramic Components
08:43

Fused Filament Fabrication FFF of Metal-Ceramic Components

Published on: January 11, 2019

18.1K
A Do-it-yourself System for Scheduled Feeding of Laboratory Rodents in Their Home Cage
04:49

A Do-it-yourself System for Scheduled Feeding of Laboratory Rodents in Their Home Cage

Published on: June 6, 2025

955

Area of Science:

  • Cyber-Physical Systems (CPS)
  • Model-Driven Engineering (MDE)
  • Software Engineering
  • Control Theory

Background:

  • Model-Driven Engineering (MDE) is crucial for developing and integrating software in Cyber-Physical Systems (CPS).
  • Disciplinary silos in design (e.g., control vs. software engineering) can lead to unmet functional and non-functional requirements.
  • Existing MDE approaches may not adequately address timing-related challenges in CPS development.

Purpose of the Study:

  • To present a co-design framework addressing design gaps between control and real-time software engineering in CPS.
  • To ensure both functional and non-functional requirements are met through a unified design approach.
  • To improve the reliability and performance of CPS by integrating timing considerations early in the design process.

Main Methods:

  • A co-design framework based on timing tolerance contracts is proposed.
  • The framework involves three steps: controller design with jitter margin analysis and co-simulation, software design with schedulability analysis, and run-time verification.
  • The framework utilizes CPAL (Cyber-Physical Action Language) for model-interpretation with timing and scheduling annotations.

Main Results:

  • The framework successfully integrates control and real-time software engineering aspects.
  • Verified controller and software designs through jitter margin and schedulability analyses.
  • Demonstrated effective run-time verification of models on target systems.
  • Successfully applied to an automotive cruise control system design.

Conclusions:

  • The proposed co-design framework effectively bridges design gaps in CPS development.
  • Timing tolerance contracts are valuable for ensuring system-wide requirements are met.
  • The framework enhances the development process for complex Cyber-Physical Systems.