Fault-Tolerant neural control for discrete-time nonlinear systems

Abstract

Development of resilient and fault-tolerant systems is particularly important in applications such as industrial processes, transportation systems, medical devices, robotic systems, and many other specialized domains that must guarantee an acceptable level of normal operation

despite their inherent complexity and the possible presence of faults. On the other hand, traditional modeling, classification, and estimation methodologies typically require the availability of a detailed mathematical characterization of the problem under study. This requirement can delay and complicate system design. As an alternative, there has been

growing interest in the development of data-driven models, which are frequently designed using artificial intelligence approaches. However, these models are commonly trained offline, which may limit their adaptability in dynamic environments. In this work, we present an online

fault-tolerant approach for uncertain nonlinear systems based on artificial neural networks designed for real-time implementations.

Bio: 

Dr. Alma Y. Alanis. received the M.Sc. and the Ph.D. degrees in electrical engineering from the Advanced Studies and Research Center of the National Polytechnic Institute (CINVESTAV-IPN), Guadalajara Campus, Mexico, in 2004 and 2007, respectively. Since 2008 she has been with University of Guadalajara, where she is currently a Dean of the Technologies for Cyber-Human Interaction Division, CUCEI. She is also a member of the Mexican National Research System (SNI-3) and member of the Mexican Academy of Sciences. She has published papers in recognized International Journals and Conferences, besides eighth international books. She is a Senior Member of the IEEE and Subject Editor of the Journal of Franklin Institute, Section Editor at Open Franklin, Technical editor at ASME/IEEE Transactions on Mechatronics and Associate Editor at IEEE transaction on Cybernetics, Intelligent Automation & Soft Computing and Action Editor for Elsevier Neural Networks, moreover she is currently serving on a number of IEEE and IFAC Conference Organizing Committees. Her research interest centers on artificial neural networks, learning systems, intelligent control, intelligent systems and its applications to biomedical systems, robotics, mechatronics and renewable energy.