This book investigates the integration of soft computing methodologies for the effective control of non-linear dynamical systems. It details the application of hybrid intelligence systems, which combine various techniques and mathematical models, to address complex control challenges. The author covers foundational concepts in fuzzy logic, neural networks, evolutionary computation, and chaos and fractal theory, presenting detailed hybrid architectures for intelligent control systems. These systems are then applied to diverse fields including robotics, reactor control, manufacturing processes, aircraft systems, and economic modeling.

The book is recognized for its comprehensive approach to applying soft computing techniques to non-linear dynamical systems. Its strength lies in detailing hybrid intelligence systems that integrate diverse methodologies, offering practical frameworks for complex control problems. The inclusion of foundational concepts alongside advanced applications makes it a valuable resource for researchers and practitioners in fields ranging from robotics to economics. The text is structured to provide both theoretical understanding and applied insights into intelligent control.