Abstract
There is the extensive usage of traditional integer order proportional-integral-derivative (PID) control methods in industrial control systems. Recently, there is a more focus on the researcher to explore the fractional order control method. Increased flexibility in designing of control system considering its derivative and integral terms can be provided by fractional order controller. The present study discusses the fractional-order control method's performance augmented by a Smith predictor structure for a first-order plus dead time (FOPDT) process. The performance of the controller was studied using a pilot pressure control plant under fractional order, integer order, and fractional order with a Smith predictor structure. The performance of each type is studied for the proposed process through simulation. The findings indicated better performance of fractional-order controllers with the Smith predictor structure.
| Original language | English |
|---|---|
| Title of host publication | 2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 700-704 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350332568 |
| DOIs | |
| State | Published - 2023 |
| Event | 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023 - Mahdia, Tunisia Duration: 20 Feb 2023 → 23 Feb 2023 |
Publication series
| Name | 2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023 |
|---|
Conference
| Conference | 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023 |
|---|---|
| Country/Territory | Tunisia |
| City | Mahdia |
| Period | 20/02/23 → 23/02/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Differential Calculus
- Fractional Integral
- Fractional Order
- Pressure Control
- Smith Predictor
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Networks and Communications
- Information Systems
- Signal Processing
- Health Informatics
- Instrumentation
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