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

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

465
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...
465
PD Controller: Design01:26

PD Controller: Design

729
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,...
729
Methods of Medium Optimization01:28

Methods of Medium Optimization

58
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
58
Control Systems01:10

Control Systems

2.0K
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...
2.0K
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

851
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
851
PID Controller01:19

PID Controller

964
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...
964

You might also read

Related Articles

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

Sort by
Same author

Ginsenoside Rg1 alleviates ANIT-induced cholestatic liver injury by inhibiting hepatic inflammation and oxidative stress via SIRT1 activation.

Journal of ethnopharmacology·2023
Same author

A general design of pyridinium-based fluorescent probes for enhancing two-photon microscopy.

Biosensors & bioelectronics·2023
Same author

Improved figure of merit (z) at low temperatures for superior thermoelectric cooling in Mg<sub>3</sub>(Bi,Sb)<sub>2</sub>.

Nature communications·2023
Same author

IL-33 Downregulates Hepatic Carboxylesterase 1 in Acute Liver Injury via Macrophage-derived Exosomal miR-27b-3p.

Journal of clinical and translational hepatology·2023
Same author

Development of a dual targeting scaffold of SET7/MLL inhibitor for castration-resistant prostate cancer treatment.

Genes & diseases·2023
Same author

The Structure of Terbium in the Ferromagnetic State.

Journal of the American Chemical Society·2023
Same journal

Stackelberg differential game-based fuzzy adaptive hierarchical optimal control for a nonlinear system with unknown dynamics.

ISA transactions·2026
Same journal

Composite fault-tolerant predictive control strategy for PMSM demagnetization faults.

ISA transactions·2026
Same journal

Bias-compensated Q-learning for optimal tracking control under denial-of-service attacks.

ISA transactions·2026
Same journal

Motion prediction for leader manipulator of teleoperation system with large time delay based on inverse optimal control.

ISA transactions·2026
Same journal

Neural network parameter identification-based prescribed-time adaptive control for morphing glide aircraft.

ISA transactions·2026
Same journal

Nonlinear system-guided continuous-time generalization for cross-aircraft engine state monitoring.

ISA transactions·2026
See all related articles

Related Experiment Video

Updated: Apr 8, 2026

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

3.1K

Fast engineering optimization: A novel highly effective control parameterization approach for industrial dynamic

Ping Liu1, Guodong Li1, Xinggao Liu1

  • 1State Key Laboratory of Industrial Control Technology, Department of Control Science & Engineering, Zhejiang University, Hangzhou 310027, China.

ISA Transactions
|June 29, 2015
PubMed
Summary
This summary is machine-generated.

A new fast control vector parameterization (fast-CVP) method significantly improves engineering optimization efficiency for industrial dynamic processes by reducing computation time by over 90% compared to traditional CVP.

Keywords:
Control vector parameterizationDynamic optimizationFast engineering optimizationNonlinear systems

More Related Videos

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.8K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

8.2K

Related Experiment Videos

Last Updated: Apr 8, 2026

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

3.1K
A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.8K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

8.2K

Area of Science:

  • Engineering Optimization
  • Industrial Dynamic Processes
  • Nonlinear Programming

Background:

  • Control Vector Parameterization (CVP) is crucial for industrial dynamic process optimization.
  • Traditional CVP suffers from low efficiency due to repeated differential equation calculations in nonlinear programming (NLP).

Purpose of the Study:

  • To introduce a novel, highly effective control parameterization approach, fast-CVP.
  • To enhance optimization efficiency for industrial dynamic processes.

Main Methods:

  • Employed costate gradient formulae.
  • Presented a fast approximate scheme to solve differential equations in dynamic process simulation.
  • Validated using three engineering optimization benchmark problems.

Main Results:

  • The fast-CVP approach achieved significant computational time savings.
  • At least 90% of computation time was saved compared to traditional CVP.
  • Demonstrated fine performance on benchmark problems.

Conclusions:

  • The proposed fast-CVP method is highly effective for industrial dynamic process optimization.
  • Fast-CVP overcomes the efficiency limitations of traditional CVP.
  • This approach offers substantial time savings for engineering optimization tasks.