The book presents a variety of state-of-the-art methods for the control of complex systems. These methods cover the theory and applications of complex dynamical systems. Given the presence of modeling uncertainties, the unavailability of the model, and the possibility of cooperative/noncooperative goals and malicious attacks compromising the security of networked systems, there is a need for novel approaches to respond to situations not programmed or anticipated in the design. This book has five sections. The first section provides an introduction to complex systems and background on the control mechanisms that will be used in the subsequent sections of the book to solve several problems. The second section provides techniques from adaptive control and neuroscience. Several adaptive learning algorithms from different perspectives are presented in the third section. Cyber-physical systems are an example of complex dynamical systems, and cooperative control for such systems is included as a collection of chapters in the fourth section. Finally, the fifth section provides real-world examples of complex systems.