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Time-Domain Interpretation of PD Control01:07

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...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
PD Controller: Design01:26

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,...
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
PID Controller01:19

PID Controller

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...
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...

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Related Experiment Video

Updated: Jul 10, 2026

A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease
04:23

A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease

Published on: April 28, 2019

Optimal control strategies and parameter estimation with a time delay dengue model using Penang Hospital data.

Shah Zeb1, Siti Ainor Mohd Yatim2,3, Daniyal-Ur Rehman4

  • 1School of Distance Education, Universiti Sains Malaysia, 11800, Minden, Malaysia.

Scientific Reports
|July 8, 2026
PubMed
Summary

This study introduces a mathematical model for dengue transmission in Malaysia, incorporating human and mosquito incubation periods. Findings highlight eco-friendly strategies for dengue control without eliminating mosquito populations.

Keywords:
DengueGlobal stabilityParameter estimationPenang HospitalSensitivity analysisSustainable controlsTime delay

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Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction
08:36

Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction

Published on: November 1, 2018

Related Experiment Videos

Last Updated: Jul 10, 2026

A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease
04:23

A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease

Published on: April 28, 2019

Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction
08:36

Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction

Published on: November 1, 2018

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Public Health

Background:

  • Dengue fever is a significant mosquito-borne viral disease in tropical regions like Malaysia.
  • Year-round transmission, lack of specific treatments, and expanding mosquito ranges pose a global health challenge.
  • Effective control strategies are crucial for mitigating dengue's impact.

Purpose of the Study:

  • To develop and analyze a mathematical model for dengue transmission dynamics.
  • To incorporate biologically relevant time delays: human intrinsic incubation period (IIP) and vector extrinsic incubation period (EIP).
  • To evaluate the impact of these delays on dengue spread and to propose control strategies.

Main Methods:

  • Development of a time-delay SEITR-SEI mathematical model.
  • Analysis of model equilibria, basic reproduction number, and stability.
  • Parameter estimation using real hospital data from Penang General Hospital (2022-2023) via the least squares method.
  • Numerical simulation using the nonstandard finite difference (NSFD) scheme and sensitivity analysis.

Main Results:

  • The dengue-free equilibrium is stable when the basic reproduction number is less than one.
  • The extrinsic incubation period (EIP) delay suppresses transmission while maintaining mosquito populations.
  • NSFD scheme demonstrated superior numerical stability and dynamic consistency compared to the Euler method.
  • Sensitivity analysis identified key parameters influencing dengue transmission in Penang.

Conclusions:

  • Mathematical modeling with biologically motivated delays provides insights into dengue dynamics.
  • Eco-friendly and sustainable control strategies are effective in limiting dengue transmission without eradicating mosquito vectors.
  • The study offers theoretical insights and practical guidance for dengue control policies in Malaysia.