A <scp>PSO</scp> ‐Based Internal Model Control Approach for Stability Enhancement in Cascade Processes

ABSTRACT This study presents a robust control strategy for unstable cascade processes with time delays, integrating Particle Swarm Optimization (PSO) and the Internal Model Control (IMC) framework. The proposed methodology employs a dual‐controller architecture, where the secondary controller is systematically tuned using the IMC approach, while the primary controller is optimized via PSO to enhance closed‐loop stability and performance. Extensive simulation studies were conducted across various unstable cascade processes to evaluate the effectiveness of the proposed approach in both servo and regulatory tasks. Comparative analysis with state‐of‐the‐art control methodologies demonstrates that the proposed strategy achieves superior closed‐loop performance, particularly in handling system uncertainties. A comprehensive numerical assessment using multiple performance indices indicates a substantial reduction in total error by 65% and control effort by 43%. The evaluation metrics include error minimization, total variation, rise time, and overshoot percentage, affirming the efficacy and robustness of the proposed control scheme.

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Publication Details

Journal
Advanced Control for Applications
Published
2025-11-06
DOI
https://doi.org/10.1002/adc2.70031
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
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article

A PSO ‐Based Internal Model Control Approach for Stability Enhancement in Cascade Processes

Chandra Shekar Besta, Raju Yerolla, Suhailam Pullanikkattil
Advanced Control for Applications
Advanced Control Systems Optimization
article

A PSO ‐Based Internal Model Control Approach for Stability Enhancement in Cascade Processes

Chandra Shekar Besta, Raju Yerolla, Suhailam Pullanikkattil
article en

Abstract

ABSTRACT This study presents a robust control strategy for unstable cascade processes with time delays, integrating Particle Swarm Optimization (PSO) and the Internal Model Control (IMC) framework. The proposed methodology employs a dual‐controller architecture, where the secondary controller is systematically tuned using the IMC approach, while the primary controller is optimized via PSO to enhance closed‐loop stability and performance. Extensive simulation studies were conducted across various unstable cascade processes to evaluate the effectiveness of the proposed approach in both servo and regulatory tasks. Comparative analysis with state‐of‐the‐art control methodologies demonstrates that the proposed strategy achieves superior closed‐loop performance, particularly in handling system uncertainties. A comprehensive numerical assessment using multiple performance indices indicates a substantial reduction in total error by 65% and control effort by 43%. The evaluation metrics include error minimization, total variation, rise time, and overshoot percentage, affirming the efficacy and robustness of the proposed control scheme.

Advanced Control for ApplicationsVol. 7(4)
National Institute of Technology Calicut (IN), University of Mysore (IN)
Openalex Percentile: Top 58%
Advanced Control Systems Optimization
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