Controller Design for Industrial Applications

Controller Design for Industrial Applications is essential for anyone looking to master the advanced techniques of intelligent controller design, enabling you to effectively tackle the complexities of modern industrial processes and optimize performance in an ever-evolving landscape.

Industrial processes are often complex and dynamic, making it challenging to design controllers that can maintain stable and optimal operation. Traditional controllers, such as PID controllers, have been widely used in industrial applications but have limitations in handling non-linear and uncertain systems. Intelligent controllers offer an alternative solution that can adapt to changing system dynamics and disturbances. The use of intelligent controllers in industrial applications has gained increasing attention in recent years, with numerous successful implementations in various fields, such as process control, robotics control, HVAC control, power systems control, and autonomous vehicle control. However, the design and implementation of intelligent controllers require careful consideration of hardware and software requirements, as well as simulation and testing procedures to ensure reliable and safe operation.

In the rapidly evolving industrial landscape, it is essential to develop advanced control techniques to enhance productivity, minimize costs, and ensure safety. Traditional control methods often struggle to handle complex systems and unpredictable environments. However, with the emergence of intelligent control techniques, there is a great opportunity to improve industrial automation and control systems. Controller Design for Industrial Applications aims to provide a comprehensive understanding of intelligent controller design for industrial applications, from theoretical concepts to practical implementation. It will cover the fundamental concepts of intelligent control theory and techniques, their application in various industrial fields, and practical implementation and design considerations.

Arindam Mondal, PhD, is a co-private investigator for a Technology Development Program project under the Indian Department of Science and Technology. He has published 33 research papers in reputed international journals, conferences, and book chapters and has 12 patents published in his credit. His research interests include digital controller design, system identification, fractional order control and signal processing, Internet of Things, bioinformatics, load frequency control, and quantum computing.

Souvik Ganguli, PhD, is an assistant professor at the Thapar Institute of Engineering and Technology, Patiala. He has published 17 papers in international journals, 36 SCOPUS-indexed papers, book chapters, and conference papers, and has been granted nine Indian patents, four German patents, and two South African patents. His research interests include model order reduction, identification and control, nature-inspired metaheuristic algorithms, electronic devices, and renewable energy applications.