Yong-duan Song, Chongqing University, China
On the “GERA” features of neuroadaptive control and robust adaptive control
Most practical engineering systems are highly nonlinear and complex in nature, posing significant technical challenge for control design. The two typical well-known control methods to deal with system nonlinearities and uncertainties are Neural Network (NN)-based Control and Robust Adaptive Control. Naturally, an interesting worthy of examining is: “for a given dynamic system with modeling uncertainties and external disturbances, would the neural network based control outperform other type of control such as robust adaptive control?” This talk will explicitly address such issue from analytical and experimental perspectives. The focus will be on comparing the “GEAR” features between those two types of control schemes, i.e., generality, effectiveness, affordability and reliability, in addition to user-friendliness and simplicity.
Bio: Yong-duan Song received his Ph.D. degree in Electrical and Computer Engineering from Tennessee Technological University, Cookeville, USA, in 1992. He held a tenured Full Professor position with North Carolina A&T State University, Greensboro, from 1993 to 2008 and a Langley Distinguished Professor position with the National Institute of Aerospace, Hampton, VA, from 2005 to 2008.
He is now the Dean of School of Automation, Chongqing University, China and the Founding Director of the Institute of Smart Systems and Renewable Energy, Chongqing University. He was one of the six Langley Distinguished Professors with the National Institute of Aerospace (NIA), and Founding Director of Cooperative Systems at NIA. He has served as an Associate Editor/Guest Editor for several prestigious scientific journals, including IEEE Trans. On Automatic Control, IEEE Trans. On Neural Networks and Learning Systems, IEEE Trans. On Intelligent Transportation Systems, IET Control Theory and Applications and others.
Prof. Song has received several competitive research awards from the National Science Foundation, the National Aeronautics and Space Administration, the U.S. Air Force Office, the U.S. Army Research Office, and the U.S. Naval Research Office. His research interests include intelligent systems, guidance navigation and control, bio-inspired adaptive and cooperative systems, rail traffic control and safety, and smart grid.