Refining PI/PID Controller Design with Stability Margins: A Survey on Simplicity and Flexibility

PI/PID controllers are widely used in power systems and the process industry, which highlights their importance because of their versatility, simplicity, and ease of installation. Despite this, the tuning of PI/PID controllers is still a rich area of study, with modern techniques building on foundational methods like those developed by Ziegler-Nichols. Because industrial processes are diverse and complicated, many techniques, including Cohen-Coon, internal model control, and error-integral criteria, have been developed over time to address specific control objectives. It is essential to comprehend the dynamics and behavior of the process in order to develop an efficient control system. This entails determining the kind of process and choosing the right design strategies to satisfy specific system requirements, like robustness, noise reduction, disturbance rejection, and set-point tracking. Achieving the required control outcomes is made flexible by the range of control designs available, including Smith predictors, internal model control, and unity negative feedback.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/icisaa62385.2024.10828995
Primary Topic
Advanced Control Systems Design
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Refining PI/PID Controller Design with Stability Margins: A Survey on Simplicity and Flexibility

Anand Kumar, Priya Kumari
Advanced Control Systems Design
article

Refining PI/PID Controller Design with Stability Margins: A Survey on Simplicity and Flexibility

Anand Kumar, Priya Kumari
article en

Abstract

PI/PID controllers are widely used in power systems and the process industry, which highlights their importance because of their versatility, simplicity, and ease of installation. Despite this, the tuning of PI/PID controllers is still a rich area of study, with modern techniques building on foundational methods like those developed by Ziegler-Nichols. Because industrial processes are diverse and complicated, many techniques, including Cohen-Coon, internal model control, and error-integral criteria, have been developed over time to address specific control objectives. It is essential to comprehend the dynamics and behavior of the process in order to develop an efficient control system. This entails determining the kind of process and choosing the right design strategies to satisfy specific system requirements, like robustness, noise reduction, disturbance rejection, and set-point tracking. Achieving the required control outcomes is made flexible by the range of control designs available, including Smith predictors, internal model control, and unity negative feedback.

Indian Institute of Technology Dhanbad (IN), Dr. D. Y. Patil Medical College, Hospital and Research Centre (IN)
University of Pune
Openalex Percentile: Top 69%
Advanced Control Systems Design
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