Intelligent Adaptive Control with System Constraints: Evolving Neural Network Approaches for Robust Adaptive Control - Tapa dura

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Radhakant Padhi is currently a higher academic grade full Professor at the Department of Aerospace Engineering and also an Associate faculty at the Centre for Cyber-Physical Systems, Indian Institute of Science (IISc), Bengaluru, India. His research interests include optimal and nonlinear control synthesis algorithms and their applications to challenging practical problems in aerospace, biomedical, and mechanical engineering. He is a Fellow of the Indian National Academy of Engineers, Aeronautical Society of India, Astronautical Society of India, and several other professional bodies. As of 2026, Prof. Padhi has co-authored approximately 300 peer-reviewed publications and three books. He has given numerous keynote and motivational speeches as well.

Ahmad Jobran Al-Mahasneh is currently an Assistant Professor in the Department of Mechatronics Engineering at Philadelphia University, Jordan. He earned his B.Sc. and M.Sc. degrees in Mechatronics/Mechanical Engineering from the Jordan University of Science and Technology in 2010 and 2014, respectively. He received his PhD in Mechanical Engineering from the University of New South Wales, Australia, in 2020. He earned the UNSW Dean’s Award for Outstanding PhD thesis. He has taught a wide range of courses, including System Dynamics, Machine Intelligence, Digital Control, Applied Nonlinear Control, Robotics, and Programmable Logic Controllers (PLC). He has also supervised numerous undergraduate projects and graduate theses in the areas of control systems, robotics, energy management systems, and mobile robotics. His research interests span adaptive and intelligent control, evolving systems, neural networks and deep learning, nonlinear control, energy management systems, and autonomous systems. 

Sreenatha Anavatti is an Academic faculty member with the University of New South Wales (UNSW) at Canberra, Australia, in the School of Engineering and Technology. Before joining UNSW, he was an Associate Professor at the Indian Institute of Technology (IIT), Mumbai, India. He received his PhD from the Indian Institute of Science (IISc), Bengaluru. Dr. Sreenatha’s research interests include guidance and control of autonomous systems as applied to Uncrewed Aerial Vehicles, Uncrewed Ground Vehicles, and Underwater Vehicles. His works include both theoretical and experimental aspects applied to autonomous systems. He has been working with Fuzzy and neural systems, evolutionary control systems, nonlinear dynamic systems and their applications, and physics-informed neural networks as applied to control. He has co-authored more than 300 publications in these areas. He has supervised more than 25 PhD scholars in these domains.  He has given numerous keynote and motivational speeches.

Kapil Sachan is currently a Senior Scientist in the Flight Mechanics and Control Division at National Aerospace Laboratories, Bangalore. He obtained both his Master of Engineering in Aerospace Engineering and his PhD from the Indian Institute of Science (IISc), Bangalore, with a specialisation in control systems theory. Dr. Sachan’s research encompasses both theoretical and applied aspects of aerospace control systems. His core areas of expertise include guidance and control of aircraft and space vehicles, nonlinear adaptive control, optimal control, and safety-constrained adaptive control. He has published in several international journals and conferences and serves as a reviewer for several scientific journals.

De la contraportada

This book provides a comprehensive overview of Adaptive control system design, with a particular emphasis on the recent advancements, covering important practical aspects such as quick adaptation without high transients, adaptation within applicable constraints on system states and control, and model-free adaptive control with smart neural networks. Standard topics in adaptive control and important introductory materials on topics such as Nonlinear system stability using Lyapunov theory are also included in this book. This book provides a clear understanding and an expedited learning experience of both fundamental and advanced topics in Intelligent Adaptive Control to students, faculty, control scientists, and practising engineers interested in designing useful Adaptive control solutions for challenging practical problems. Numerous illustrative problems are included in this book to facilitate a better understanding of the concepts presented. This book is a useful guide for those interested in advanced and evolving topics in adaptive control.