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

Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

606
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
606
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

432
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
432
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.0K
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
1.0K
Modeling with Differential Equations01:25

Modeling with Differential Equations

138
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
138
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

454
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
454
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

387
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,...
387

You might also read

Related Articles

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

Sort by
Same author

ARX model decomposed on Meixner-Like orthonormal bases.

ISA transactions·2019
Same author

New methods of Laguerre pole optimization for the ARX model expansion on Laguerre bases.

ISA transactions·2017
Same author

Nonlinear system modeling based on bilinear Laguerre orthonormal bases.

ISA transactions·2013
Same author

Decomposition of an ARX model on Laguerre orthonormal bases.

ISA transactions·2012

Related Experiment Video

Updated: Mar 10, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.9K

Adaptive MPC based on MIMO ARX-Laguerre model.

Imen Ben Abdelwahed1, Abdelkader Mbarek1, Kais Bouzrara1

  • 1Research Laboratory of Automatic Signal and Image Processing, National School of Engineers of Monastir, University of Monastir, 5019, Tunisia.

ISA Transactions
|December 13, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive predictive control method using a simplified MIMO ARX-Laguerre model. This approach enables real-time implementation by avoiding complex optimization, demonstrated on a CSTR process.

Keywords:
ARX-Laguerre modelAdaptive predictive controlMIMO system modelingOnline identificationPole optimization

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

2.2K

Related Experiment Videos

Last Updated: Mar 10, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.9K
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

2.2K

Area of Science:

  • Control Engineering
  • Process Systems Engineering
  • Computational Modeling

Background:

  • Model complexity is a significant challenge in implementing advanced control strategies.
  • Traditional linear predictive control often requires computationally intensive optimization algorithms.
  • Real-time adaptive control is crucial for dynamic industrial processes.

Purpose of the Study:

  • To develop a computationally efficient method for synthesizing adaptive predictive controllers.
  • To utilize a reduced-complexity model for improved real-time performance.
  • To validate the proposed method on a standard chemical process benchmark.

Main Methods:

  • A Multi-Input Multi-Output (MIMO) ARX model is projected onto Laguerre bases, creating a reduced-complexity MIMO ARX-Laguerre model.
  • Adaptive predictive control laws are derived using multi-step-ahead finite-element predictors identified from experimental data.
  • Online identification algorithms are employed to tune model parameters and Laguerre poles iteratively.

Main Results:

  • The MIMO ARX-Laguerre model offers an easily representable recursive structure.
  • The proposed control strategy avoids time-consuming numerical optimization, facilitating real-time application.
  • Successful synthesis and simulation of adaptive predictive controllers for the CSTR process benchmark were achieved.

Conclusions:

  • The proposed method provides an efficient and practical approach for real-time adaptive predictive control.
  • Reduced-order modeling using Laguerre bases significantly enhances computational feasibility.
  • The technique is well-suited for controlling complex dynamic systems like the CSTR.