Iterative learning control (ILC) has been a major control design methodology for twenty years. Numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterized by repetitive control operations. Real-time iterative learning control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a systematic introduction to real-time ILC design and a source of illustrative case studies for ILC problem solving. The fundamental concepts, schematics, configurations, and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple, and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed.