Neural Networks For Modelling And Control of Dynamic Systems

Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights.

This book covers recent advances of machine learning techniques in a broad range of applications in smart cities, automated industry, and emerging businesses.

This book is the result of inspirations and contributions from many researchers worldwide. It presents a collection of wide range research results of robotics scientific community. Various aspects of current research in robotics area are explored and discussed. Different mechatronic systems oriented on robotics are explored in the book.