Modelling Dynamic Systems with Artificial Neural Networks and Related Methods

The book Modelling Dynamic Systems with Artificial Neural Networks and Related Methods can be used as a textbook for the field it covers or as introductory professional literature that serves as an initial reading for more advanced literature in this field. The textbook provides an introduction to artificial neural networks, the identification of linear and nonlinear dynamic systems, control with artificial neural networks, local-model networks and blended multiple-model systems, the design of gain-scheduling control, and the identification of nonlinear systems using Gaussian processes. It is intended for students, especially at the postgraduate level, who have sufficient prior knowledge of dynamic systems, and for experts with the appropriate previous knowledge for self-study and familiarisation with the concepts and views described. The book is not intended to be a detailed theoretical description of the field, but rather an overview of dynamic-systems identification using neural networks and related methods from the perspective of dynamic systems theory, with a primary focus on their applications. The work aims to familiarise the reader with the views on this issue, which are treated differently by various disciplines, despite their related nature.