Fractional-order Systems and PID Controllers: Using Scilab and Curve Fitting Based Approximation Techniques: 264 (Studies in Systems, Decision and Control, 264) - Softcover

Bingi, Kishore; Ibrahim, Rosdiazli; Karsiti, Mohd Noh; Hassan, Sabo Miya; Harindran, Vivekananda Rajah

 
9783030339364: Fractional-order Systems and PID Controllers: Using Scilab and Curve Fitting Based Approximation Techniques: 264 (Studies in Systems, Decision and Control, 264)
Softcover
ISBN 10: 303033936X ISBN 13: 9783030339364
Publisher: Springer, 2020

Synopsis

This book presents a detailed study on fractional-order, set-point, weighted PID control strategies and the development of curve-fitting-based approximation techniques for fractional-order parameters. Furthermore, in all the cases, it includes the Scilab-based commands and functions for easy implementation and better understanding, and to appeal to a wide range of readers working with the software. The presented Scilab-based toolbox is the first toolbox for fractional-order systems developed in open-source software. The toolboxes allow time and frequency domains as well as stability analysis of the fractional-order systems and controllers. The book also provides real-time examples of the control of process plants using the developed fractional-order based PID control strategies and the approximation techniques. The book is of interest to readers in the areas of fractional-order controllers, approximation techniques, process modeling, control, and optimization, both in industry and academia. In industry, the book is particularly valuable in the areas of research and development (R&D) as well as areas where PID controllers suffice – and it should be noted that around 80% of low-level controllers in industry are PID based. The book is also useful where conventional PIDs are constrained, such as in industries where long-term delay and non-linearity are present. Here it can be used for the design of controllers for real-time processes. The book is also a valuable teaching and learning resource for undergraduate and postgraduate students.

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From the Back Cover

This book presents a detailed study on fractional-order, set-point, weighted PID control strategies and the development of curve-fitting-based approximation techniques for fractional-order parameters. Furthermore, in all the cases, it includes the Scilab-based commands and functions for easy implementation and better understanding, and to appeal to a wide range of readers working with the software. The presented Scilab-based toolbox is the first toolbox for fractional-order systems developed in open-source software. The toolboxes allow time and frequency domains as well as stability analysis of the fractional-order systems and controllers. The book also provides real-time examples of the control of process plants using the developed fractional-order based PID control strategies and the approximation techniques. The book is of interest to readers in the areas of fractional-order controllers, approximation techniques, process modeling, control, and optimization, both in industry and academia. In industry, the book is particularly valuable in the areas of research and development (R&D) as well as areas where PID controllers suffice – and it should be noted that around 80% of low-level controllers in industry are PID based. The book is also useful where conventional PIDs are constrained, such as in industries where long-term delay and non-linearity are present. Here it can be used for the design of controllers for real-time processes. The book is also a valuable teaching and learning resource for undergraduate and postgraduate students.

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Publisher
Springer
Publication date
2020
Language
English
ISBN 10 
303033936X
ISBN 13 
9783030339364
Binding
Paperback
Edition number
1
Number of pages
272

Other Popular Editions of the Same Title

9783030339333: Fractional-order Systems and PID Controllers: Using Scilab and Curve Fitting Based Approximation Techniques: 264 (Studies in Systems, Decision and Control, 264)

Featured Edition

ISBN 10:  3030339335 ISBN 13:  9783030339333
Publisher: Springer, 2019
Hardcover