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 Experiment Videos

Solution of low-dimensional constrained model predictive control problems.

Yash P Gupta1

  • 1Department of Chemical Engineering, Dalhousie University, Halifax, NS, Canada.

ISA Transactions
|November 13, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A closed-loop cross-correlation method for detecting model mismatch in MIMO model-based controllers.

ISA transactions·2008
Same author

Control of nonlinear processes by using linear model predictive control algorithms.

ISA transactions·2008
Same author

Solution of nonlinear optimal control problems using a semi-exhaustive search.

ISA transactions·2007
Same author

Robust and nominal stability conditions for a simplified model predictive controller.

ISA transactions·2006
Same author

A simplified predictive control algorithm for disturbance rejection.

ISA transactions·2005
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
Same journal

Predefined-time distributed optimal formation control for constrained UAV-UGV systems.

ISA transactions·2026
Same journal

Fixed-time distributed secondary control for voltage/frequency restoration and power sharing in microgrids under switching topologies.

ISA transactions·2026
Same journal

A robust ATUB-Net for bearing fault diagnosis under unbalanced sample scenarios.

ISA transactions·2026
Same journal

Data-driven trajectory tracking control of UAV systems under a novel probability-selection event-triggered mechanism.

ISA transactions·2026
See all related articles

Model predictive control (MPC) benefits from solving optimization problems. A new method visualizes the relationship between constrained and unconstrained optima, simplifying solutions for low-dimensional systems.

Area of Science:

  • Control Engineering
  • Optimization Theory

Background:

  • Model predictive control (MPC) offers significant benefits through solving constrained optimization problems.
  • Existing methods for specific MPC problems can be computationally intensive.

Purpose of the Study:

  • To visualize the relationship between constrained and unconstrained optima in MPC.
  • To propose a computationally efficient method for finding the constrained optimum in low-dimensional control systems.

Main Methods:

  • The study visualizes the relationship between constrained and unconstrained optimal solutions.
  • A novel method is developed based on this visualized relationship.

Main Results:

  • The proposed method effectively finds the constrained optimum for low-dimensional systems.

Related Experiment Videos

  • Computational effort was reduced by 10-35 times compared to linear programming for 2x2 and 3x3 problems.

    • Conclusions:

    • The developed method offers a computationally efficient alternative for solving constrained optimization problems in MPC.
    • This approach enables the utilization of MPC benefits in small-scale process control systems already installed in plants.