Control of Complex Systems: Theory and Applications contains a collection of articles by friends, co-authors, colleagues, and former PhD students of Frank L. Lewis. The 25 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, and control. The editors have grouped these into the following five sections: Background and Open Topics, Adaptive Control and Neuroscience, Adaptive Learning Algorithms for Control and Diagnosis, Cooperative Control, Applications and Other Related Topics. The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is for researchers and control engineers working with machine learning, adaptive control, and automatic control systems, including electrical engineers, computer science engineers, mechanical engineers, aerospace/automotive engineers, and industrial engineers. It could be used as a text or reference for advanced courses in learning and adaptive control systems, or learning feedback control.
Includes chapters from several well-known professors and researchers that showcases their recent workPresents different state-of-the-art control approaches and theory for complex systemsExplores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teamsServes as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems
