This book is intended for researchers and control engineers in machine learning, adaptive control, optimization 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 complex control systems.
. Collection of chapters from several well-known professors and researchers that will showcase their recent work
. Presents different state-of-the-art control approaches and theory for complex systems
. Gives algorithms that take into consideration 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 teams
. Real system examples and figures throughout, make ideas concrete
- Includes chapters from several well-known professors and researchers that showcases their recent work
- Presents different state-of-the-art control approaches and theory for complex systems
- Explores 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 teams
- Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems
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