Adaptive control plays a critical role in modern engineering systems by enabling controllers to respond intelligently to uncertainties, disturbances, and changing operating conditions. Adaptive Control - Theory, Algorithms, and Real-World Systems presents contemporary developments in adaptive methodologies, computational algorithms, and practical implementations that support robust and high-performance system operation. Covering topics such as neural adaptive control, human-in-the-loop systems, gain scheduling, risk-aware optimization, stochastic decision-making, and dynamic parameter estimation, the book provides a multidisciplinary perspective on adaptation in complex environments. Emphasizing both theoretical foundations and practical applications, the volume demonstrates how adaptive strategies can enhance stability, accuracy, robustness, and decision-making capabilities across a variety of engineering domains. Designed for researchers, postgraduate students, practitioners, and industry professionals, this book serves as a valuable reference for understanding and applying adaptive control techniques in intelligent and real-world systems.