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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. 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. 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.

System identification.

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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. 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. 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.

System identification.

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Most of the research and experiments in the fields of modeling and control systems have spent significant efforts to find rules from various complicated phenomena by principles, observations, measured data, logic derivations. The rules are normally summarized as concise and quantitative expressions or “models”. “Identification” provides mechanisms to establish the models and “control” provides mechanisms to improve system performances. This book reflects the relevant studies and applications in the area of renewable energies, with the latest research from interdisciplinary theoretical studies, computational algorithm development to exemplary applications. It discusses how modeling and control methods such as recurrent neural network, Pitch Angle Control, Fuzzy control, Sliding Mode Control and others are used in renewable systems. It covers topics as photovoltaic systems, wind turbines, maximum power point tracking, batteries for renewable energies, solar energy, thermal energy and so on. This book is edited and written by leading experts in the field and offers an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, control system and energy.

Electricity --- Relation between energy and economics --- Electrical engineering --- Applied physical engineering --- Equipment, services, installations in buildings --- elektrische netwerken --- hernieuwbare energie --- automatisering --- elektrische machines --- elektriciteitsproductie --- elektriciteitsdistributie

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The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, researchers and practitioners in the area of soft computing, systems modeling and control.

Engineering. --- Computational Intelligence. --- Control. --- Industrial and Production Engineering. --- Statistical Physics, Dynamical Systems and Complexity. --- Complexity. --- Physics. --- Industrial engineering. --- Ingénierie --- Physique --- Génie industriel --- Engineering & Applied Sciences --- Computer Science --- Statistical physics. --- Dynamical systems. --- Computational intelligence. --- Complexity, Computational. --- Control engineering. --- Production engineering. --- Manufacturing engineering --- Process engineering --- Industrial engineering --- Mechanical engineering --- Management engineering --- Simplification in industry --- Engineering --- Value analysis (Cost control) --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Complexity, Computational --- Electronic data processing --- Machine theory --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Mathematical statistics --- Construction --- Industrial arts --- Technology --- Statistical methods --- Control and Systems Theory. --- Complex Systems. --- Statistical Physics and Dynamical Systems. --- Soft computing. --- Cognitive computing --- Computational intelligence --- Computational complexity.