Books.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Overview
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 ILC's 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 ILC's 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.
Synopsis
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 ILC's 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 ILC's 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.
Booknews
Explores a control method that exploits every possibility to incorporate past control information, such as tracking errors and control input signals, into constructing a present control action. Summarizes the status of research, points out trends to keep an eye on or a hand in, and an invitation to practicing control engineers and academic researchers to consider the merits of the method in their own research and applications. The 18 papers cover the general background, properties of the approach, design issues, integration with other intelligent control methods, and implementation. Among the topics are the high-order control of discrete-time nonlinear systems using current iteration tracking error, designing iterative learning and repetitive controllers, model-reference learning control with a wavelet network, gas-metal arc welding, and functional neuromuscular simulation. Annotation c. by Book News, Inc., Portland, Or.