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

Buch 221 von 378: Studies in Systems, Decision and Control

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 (Studies in Systems, Decision and Control, Band 264)

Inhaltsangabe

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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Über die Autorin bzw. den Autor

Dr. Kishore Bingi is a Senior Lecturer in the Electrical and Electronic Engineering Department at Universiti Teknologi PETRONAS (UTP), Malaysia. He obtained his Bachelor of Technology in Electrical and Electronics Engineering from Acharya Nagarjuna University, India 2012, followed by a Master of Technology in Instrumentation and Control Systems from the National Institute of Technology Calicut, India, in 2014. He earned his PhD in Process Control and Automation from UTP in 2019. After completing his doctorate, Dr. Bingi served as a Research Scientist and Postdoctoral Researcher at UTP's Institute of Autonomous Systems from February 2019 to May 2020. He subsequently joined Vellore Institute of Technology, India, as an Assistant Professor (Senior Grade) in the School of Electrical Engineering, a role he held from June 2020 to September 2022. In November 2022, he returned to UTP as a Lecturer. Dr Bingi's research expertise spans control and automation, process modelling, optimization, fractional-order systems and controllers, fractional-order neural networks, and forecasting. His professional affiliations include membership in the Institute of Electrical and Electronics Engineers (IEEE), the Institution of Engineering and Technology (IET), and the Asian Control Association (ACA). Additionally, he holds the prestigious designation of Chartered Engineer from the Engineering Council, UK.

Bhukya Ramadevi earned her Bachelor of Technology in Electrical and Electronics Engineering from Acharya Nagarjuna University, India, in 2018. She subsequently obtained her Master of Technology in Advanced Power Systems from Jawaharlal Nehru Technological University, India, in 2020. She completed her PhD in the School of Electrical Engineering at Vellore Institute of Technology (VIT), India. Her research focuses on developing fractional-order neural networks and fractional-order long short-term memory (LSTM) networks for time series forecasting and prediction. In addition to her research, she serves as a Teaching cum Research Assistant at VIT Vellore. Her areas of expertise include artificial intelligence, fractional calculus, control and automation, and power systems.

Dr. Venkata Ramana Kasi received his B.Tech. degree in Electrical and Electronics Engineering from JNTU Hyderabad in 2007, followed by an M.Tech. degree in Power Systems from Birla Institute of Technology, Mesra, Ranchi, India, in 2010. He completed his PhD in Electronics and Electrical Engineering at the Indian Institute of Technology (IIT) Guwahati, India 2018. He briefly worked as a Technical Lead at KPIT Technologies, Pune, India. Since 2020, he has been serving as an Assistant Professor in the School of Electrical Engineering (SELECT) at the Vellore Institute of Technology (VIT), Vellore, India. He has published numerous research articles in reputed international journals and presented at both international and national conferences. His research interests include system identification, time-delayed systems, DC-DC converter modeling, and Li-ion battery state-of-charge (SOC) estimation.

Von der hinteren Coverseite

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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Weitere beliebte Ausgaben desselben Titels

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

Vorgestellte Ausgabe

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