this book provides a comprehensive update and overview of iterative learning control theory and techniques relevant to industrial automation, and focuses on new research directions for the 21st century. thorough, well-organized, and completely up-to-date, it examines all the important aspects of this emerging technology. iterative learning control: analysis, design, integration and applications provides dynamic coverage of ilcs history, its expanding real-world applications, and its robustness and convergence. also included are sampled-data and discrete-time issues, design guidelines and quadratic criterion, the ability of dynamic systems to learn, time-delay problem, integration (with neural network, fuzzy logic and wavelet), direct learning, and identification, in addition to ilcs possible applications to batch and welding processes, neuromuscular stimulation, and other fast-changing fields. the contributions are written by some of the leading internationally recognized researchers in ilc. iterative learning control: analysis, design, integration and applications will be of interest to researchers and engineers in robotics, automation, systems and control, and signal processing.