Adaptive-Robust Control with Limited Knowledge on Systems Dynamics (eBook)

Dr. Spandan Roy currently serves as an Assistant Professor at the Robotics Research Center, International Institute of Information Technology, Hyderabad (IIIT-H). He received his B.Tech. from West Bengal University of Technology, completed his M.Tech. in Mechatronics at the Academy of Scientific and Innovative Research, CSIR-Central Mechanical Engineering Research Institute, and received his Ph.D. at the Department of Electrical Engineering, Indian Institute of Technology, Delhi. He was a Postdoctoral Fellow at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. His main research interests are adaptive-robust control, artificial delay based design, switched systems and robotics. 

Prof. Indra Narayan Kar currently serves as a professor at the Department of Electrical Engineering, Indian Institute of Technology Delhi. He completed his B.E. at Bengal Engineering College (now known as Indian Institute of Engineering Science and Technology, Shibpur), and his M.Tech. and Ph.D. at the Indian Institute of Technology Kanpur. His research interests include nonlinear systems theory, contraction analysis, adaptive robust control, time-delay system, robust-optimal control theory, cyber-physical systems, control of multi-agent systems, and robotics. He has published many papers in his areas of interest and also co-author of few patents.

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The book investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler-Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data. The book offers a unique resource for researchers in the areas of ARC and TDC alike, and covers the state of the art, new algorithms, and future directions.