This textbook presents the comprehensive theoretical foundations and advanced concepts and applications in the fields of nonlinear neuro-control systems. The authors start with not only basic concepts of neural adaptation and learning of information storage but also with basic characteristics of feedback control systems, and proceed to introduce basic and advanced theories of feedback control systems and neural networks, such as analysis, stability, and design of continuous-time and discrete-time linear control systems and network configuration and learning of multilayer feedforward neural networks, radial basis function networks, and fuzzy neural networks. The authors continue with advanced theories and applications of nonlinear neuro-control. The theory in each chapter is illustrated by several examples, and each chapter is appended by a list of problems. Online appendices include Mathematical Foundations, Bibliography, Major Current Bibliographical Sources on Neuro-Control and Applications and Matlab? Codes