Complex Dynamic System Modelling Identification and Control

<p>The study of complex dynamic systems has become increasingly important in recent years due to its wide range of applications in fields such as engineering physics economics and biology. These systems are characterized by their interconnectedness nonlinearities and feedback loops which make them difficult to understand and control. As a result there has been growing interest in developing tools and techniques for the modelling identification and control of complex dynamic systems.</p><p>The aim of this reprint is to provide an overview of the state-of-the-art methods for the modelling identification and control of complex dynamic systems. This reprint covers a wide range of topics including system identification model-based control adaptive control nonlinear control and predictive control. It also includes case studies and examples from different fields to demonstrate the practical application of these methods.</p><p>This reprint is intended for researchers graduate students and practitioners in the field of control systems. It assumes a basic understanding of linear systems theory calculus and linear algebra. Overall this reprint provides a comprehensive and up-to-date overview of the methods for the modelling identification and control of complex dynamic systems.</p>