Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications."

"This is a thought-provoking book that will stimulate a constructive reevaluation of widespread management practices-and they badly need such reevaluation. If it does nothing else-and it does much more-it would deserve a serious reading."151;Russell L. Ackoff, Chairman, INTERACT, The Institute for Interactive Management
"Integrated Management Systems points the direction for the next leg of the quality journey by synthesizing success stories from diverse organizations into a broader set of best management practices."151;Ray Stata, Chairman, Analog Devices, Inc.
"Nothing would improve the performance of managers and organizations more than a deeper understanding of the potential and limitations inherent in management systems. This superb book, by three outstanding scholars, goes a very long way to that end."-Louis E. Lataif, Dean, Boston University School of Management
"A vast reservoir of diverse and profoundly rich experience with some of the most respected institutions such as GE, MIT, and IIASA has set Tom Lee up in pursuit of a lifetime dream. This book is the story of a fascinating journey in quest of a synthesis of the best management practices." -Jamshid Gharajedaghi, Managing Partner and CEO, INTERACT, The Institute for Interactive Management
"Finally, a book which offers pragmatics instead of polemics regarding the whole notion of quality and what it means to be a quality-based organization. This is no oneminute manager but a thoughtful and reflective guide to action." -Michael Lissack, Director, Organization Science-Related Programs, New England Complex Systems Institute and Editor-in-Chief, Emergence: A Journal of Complexity Issues in Organizations andManagement
"Integrated Management Systems is unique in its leadership thinking and practice. It combines the association of experience, the capacity of intelligence, and professionalism required to lead in a turbulent world." -Robert W. A. Barbour, Director and Chief Executive, Northern Ireland Quality Centre
"East meets West in Integrated Management Systems: an innovative synthesis of American systems theory and Japanese TQM practice that will become the standard reference text for researchers and practitioners everywhere." -Dr. Eamonn Murphy, Director, National Centre for Quality Management University of Limerick, Ireland

Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications."