Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes.
In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their application in meaningful areas, such as electric three phase induction motors and anaerobic process, which show the applicability of such designs. The proposed schemes can be employed for different applications beyond those presented.
The book presents solutions for the state estimation problem of unknown nonlinear systems based on two schemes. For the first one, a full state estimation problem is considered; the second one considers the reduced order case with, and without, the presence of unknown delays. Both schemes are developed in discrete-time using recurrent high order neural networks in order to design the neural observers, and the online training of the respective neural networks is performed by Kalman Filtering.
- Presents online learning for Recurrent High Order Neural Networks (RHONN) using the Extended Kalman Filter (EKF) algorithm
- Contains full and reduced order neural observers for discrete-time unknown nonlinear systems, with and without delays
- Includes rigorous analyses of the proposed schemes, including the nonlinear system, the respective observer, and the Kalman filter learning
- Covers real-time implementation and simulation results for all the proposed schemes to meaningful applications
Research Engineers working on artificial neural networks, control systems and electric machinery control, Biomedical Engineers, Biomechanical Engineers, and Electrical Engineers
Chapter 1: Introduction
- 1.1. Introduction
- 1.2. Motivation
- 1.3. Objectives
- 1.4. Problem Statement
- 1.5. Book Structure
- 1.6. Notation
Chapter 2: Mathematical Preliminaries
- 2.1. Stability Definitions
- 2.2. Introduction to Artificial Neural Networks
- 2.3. Discrete-Time High Order Neural Networks
- 2.4. The EKF Training Algorithm
- 2.5. Introduction to Nonlinear Observers
Chapter 3: Full Order Neural Observers
- 3.1. Linear Output Case
- 3.2. Nonlinear Output Case
- 3.3. Applications
Chapter 4: Reduced Order Neural Observers
- 4.1. Reduced Order Observers
- 4.2. Neural Identifiers
- 4.3. Linear Output Case
- 4.4. Nonlinear Output Case
- 4.5. Applications
Chapter 5: Neural Observers with Unknown Time-Delays
- 5.1. Introduction
- 5.2. Time-Delay Nonlinear System
- 5.3. Full Order Neural Observers for Unknown Nonlinear Systems with Delays
- 5.4. Reduced Order Neural Observers for Unknown Nonlinear Systems with Delays
- 5.5. Applications
Chapter 6: Final Remarks
- 6.1. Final Remarks
- No. of pages:
- © Academic Press 2017
- 7th February 2017
- Academic Press
- eBook ISBN:
- Paperback ISBN:
Alma Y. Alanis received her B. Sc degree from Instituto Tecnologico de Durango (ITD, Durango Campus, Durango, Durango) in 2002, and her M.Sc. and 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 the University of Guadalajara, where she is currently a Chair Professor in the Department of Computer Science. She is also a member of the Mexican National Research System (SNI-2). She has published papers in recognized International Journals and Conferences, along with two international books. She is a Senior Member of the IEEE and Subject and Associated Editor of the Journal of Franklin Institute (Elsevier) and Intelligent Automation & Soft Computing (Taylor & Francis); moreover, she is currently serving on a number of IEEE and IFAC Conference Organizing Committees. In 2013 she received the grant for women in science by L'Oreal-UNESCO-AMC-CONACYT-CONALMEX. In 2015, she received the Marcos Moshinsky Research Award. Since 2008, she has been a member of the Accredited Assessors record (RCEA-CONACYT), evaluating a wide range of national research projects. She has belonged to important project evaluation committees for national and international research projects. Her research interests are in neural control, backstepping control, block control, and their applications to electrical machines, power systems and robotics.
University of Guadalajara Guadalajara, Jalisco, Mexico
Edgar N. Sanchez was born in 1949, in Sardinata, Colombia, South America. He obtained his BSEE major in Power Systems from Universidad Industrial de Santander (UIS, Bucaramanga, Colombia) in 1971, his MSEE from CINVESTAV-IPN (Advanced Studies and Research Center of the National Polytechnic Institute), his major in Automatic Control (Mexico City, Mexico) in 1974, and his Docteur Ingenieur degree in Automatic Control from Institut Nationale Polytechnique de Grenoble, France in 1980.
In 1971, 1972, 1975 and 1976, he worked for different electrical engineering consulting companies in Bogota, Colombia. In 1974 he was a professor in the Electrical Engineering Department of UIS, Colombia. From January 1981 to November 1990, he worked as a researcher at the Electrical Research Institute, Cuernavaca, Mexico. He was a professor of the graduate program in electrical engineering at the Universidad Autonoma de Nuevo Leon (UANL), Monterrey, Mexico, from December 1990 to December 1996. Since January 1997, he has been with CINVESTAV-IPN (Guadalajara Campus, Mexico) as a Professor of Electrical Engineering in their graduate programs. His research interests are in neural networks and fuzzy logic as applied to automatic control systems. He has been the advisor of 21 Ph. D. theses and 40 M. Sc theses.
He was granted a USA National Research Council Award as a research associate at NASA Langley Research Center, Hampton, Virginia, USA (January 1985 to March 1987). He is also a member of the Mexican National Research System (promoted to highest rank, III, in 2005), the Mexican Academy of Science and the Mexican Academy of Engineering. He has published four books, more than 150 technical papers in international journals and conferences, and has served as a reviewer for different international journals and conferences. He has also been a member of many international conferences, both IEEE and IFAC.
Research Professor, CINVESTAV Guadalajara