Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Open and closed-loop control systems

Open and closed-loop control systems

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 and...

Feedback control systems

Feedback control systems

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...

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...

Time-Domain Interpretation of PD Control

Time-Domain Interpretation of PD Control

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...

PD Controller: Design

PD Controller: Design

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,...

You might also read

Related Articles

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

Sort by

Same author

The Association Between the STOP-Bang Score and the Integrated Pulmonary Index in Patients Undergoing Endobronchial Ultrasound with Sedation: The STOP OSA-IPI Cohort Study.

Medicina (Kaunas, Lithuania)·2026

Same author

Recombinant Expression and Bioprocess Optimization of Priestia megaterium α-Amylase and Its Impact on Dough Fermentation Efficiency.

Chemistry & biodiversity·2025

Same author

Multilocus sequence typing of <i>L. bulgaricus</i> and <i>S. thermophilus</i> strains from Turkish traditional yoghurts and characterisation of their techno-functional roles.

Food science and biotechnology·2024

Same author

Antifungal Activities of Different Essential Oils and Their Electrospun Nanofibers against <i>Aspergillus</i> and <i>Penicillium</i> Species Isolated from Bread.

ACS omega·2022

Same author

Isolation and characterization of yogurt starter cultures from traditional yogurts and growth kinetics of selected cultures under lab-scale fermentation.

Preparative biochemistry & biotechnology·2022

Same author

High level production of itaconic acid at low pH by Ustilago maydis with fed-batch fermentation.

Bioprocess and biosystems engineering·2021

Search research articles

Related Experiment Video

Updated: Jul 19, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Nonlinear predictive control of a drying process using genetic algorithms.

Ugur Yuzgec¹, Yasar Becerikli, Mustafa Turker

¹Department of Electronics and Telecommunications Engineering, Kocaeli University, 41040, Kocaeli, Turkey. uyuzgec@kou.edu.tr

ISA Transactions

|October 27, 2006

Summary

This study introduces a nonlinear predictive control method for optimizing baker's yeast drying. The technique enhances product quality, reduces energy use, and shortens drying time.

More Related Videos

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Published on: April 19, 2021

Related Experiment Videos

Last Updated: Jul 19, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Published on: April 19, 2021

Area of Science:

Process Control
Chemical Engineering
Food Science

Background:

Traditional drying processes for baker's yeast often face challenges in optimizing quality and efficiency.
Developing advanced control strategies is crucial for improving industrial drying operations.

Purpose of the Study:

To develop and apply a nonlinear predictive control (NPC) technique for optimizing the baker's yeast drying process.
To enhance manufacturing quality, reduce energy consumption, and decrease drying time.

Main Methods:

A complete nonlinear model of the baker's yeast drying process was developed for prediction.
An objective function was defined to minimize deviations between model predictions and desired trajectories.
A genetic algorithm was employed to solve the complex optimization problem inherent in the control scheme.

Main Results:

The proposed NPC method was successfully applied to the baker's yeast drying process.
Significant improvements in manufacturing quality were observed.
Substantial reductions in energy consumption and drying time were achieved.

Conclusions:

Nonlinear predictive control offers an effective strategy for optimizing industrial drying processes.
The developed method demonstrates potential for enhancing efficiency and product quality in baker's yeast production.