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Feedback control systems

Feedback control systems

Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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Related Experiment Video

Updated: Jan 26, 2026

Control of Eating Behavior Using a Novel Feedback System

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

Feedforward and Feedback Control of a Pharmaceutical Coating Process.

Yuxiang Zhao¹, James K Drennen^1,2, Shikhar Mohan¹

¹Duquesne University Graduate School of Pharmaceutical Sciences, Pittsburgh, Pennsylvania, USA.

AAPS Pharmscitech

|April 3, 2019

Summary

This study integrates feedforward and feedback control for theophylline granule coating. This advanced system effectively manages variations in granule size and conditions to achieve a consistent drug release profile.

Keywords:

feedback feedforward granule coating near-infrared process control

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Last Updated: Jan 26, 2026

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Area of Science:

Pharmaceutical Technology
Process Control
Materials Science

Background:

Controlled release drug delivery systems are crucial for optimizing therapeutic outcomes.
Fluid bed coating is a common method for applying controlled release coatings to pharmaceutical granules.
Process variability can significantly impact the quality and performance of coated granules.

Purpose of the Study:

To develop and evaluate a combined feedforward and feedback control system for theophylline granule coating.
To assess the system's ability to manage variations in granule size and environmental conditions.
To achieve a consistent and desired drug dissolution profile for the coated granules.

Main Methods:

Utilized feedforward models based on granule size distribution to set airflow and target coat weight.
Implemented a feedback loop with Near-Infrared (NIR) spectroscopy for real-time monitoring of coat weight.
Employed Monte Carlo simulations to compare control system performance with and without the feedforward component.

Main Results:

The combined control system successfully accommodated significant variations in granule size distributions and ambient conditions.
A desired dissolution profile was consistently achieved despite process variations.
Monte Carlo simulations demonstrated the critical role of the feedforward component in system performance.

Conclusions:

A hybrid feedforward-feedback control strategy is effective for robust controlled release coating of theophylline granules.
This approach enhances process consistency and ensures predictable drug release performance.
The integration of NIR spectroscopy and feedforward modeling offers a powerful tool for pharmaceutical process optimization.