About the speaker
Andrea Serrani received the laurea (B.Eng.) degree in electrical engineering, summa cum laude and the Ph.D. degree in artificial intelligence systems from the University of Ancona, Italy, in 1993 and 1997, and the M.S. and D.Sc. degrees in systems science and mathematics from Washington University, St. Louis, MO, USA, in 1996 and 2000, respectively. From 1994 to 1999, he was a Fulbright Fellowwith Washington University. Since 2002, he has been with the Department of Electrical and Computer Engineering, Ohio State University, Columbus, OH, USA, where he is currently a Professor and Associate Chair. He has held visiting positions with the University of Bologna, Bologna, Italy, and University of Padua, Padua, Italy, and multiple summer faculty fellowships with AFRL. His work has been supported by AFRL, NSF, Ford Motor Co., and NASA, among others. He has authored or coauthored more than 150 articles in journals, proceedings of international conferences, and book chapters, and is the coauthor of the book Robust Autonomous Guidance: An Internal Model Approach (Springer-Verlag). His research interests include methodological aspects of nonlinear, adaptive and geometric control theory with applications in aerospace and marine systems, fluidic systems, robotics and automotive engineering. Prof. Serrani is the Editor-in-Chief for the IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY and was an Associate Editor for the IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, from 2010 to 2016, Automatica, from 2008 to 2014, and the International Journal of Robust and Nonlinear Control, from 2006 to 2014. He serves on the Conference Editorial Boards of IEEE Control Systems Society (CSS) and International Federation of Automatic Control, served as Program Chair for the 2019 American Control Conference, and as General Co-chair for the 2022 IEEE Conference on Decision and Control. He was a Distinguished Lecturer of the IEEE CSS.
Abstract
The lectures aim at giving an introductory treatment of classic methodologies for adaptive control of linear systems. The emphasis of the course is on introducing fundamental concepts and issues in the analysis and design of adaptive control systems for SISO LTI models. Topics include: 1) Model following for SISO LTI systems: definition and certainty-equivalence solution; 2) Direct and indirect approach to synthesis; 3) Controller and plant parameterization; 4) Synthesis of the update law; 5) Stability and convergence analysis; 6) (if time allows) Robustness to external disturbances.