Iterative Learning Control: Analysis, Design, Integration and Applications - Rilegato

Rilegato

ISBN 10: 0792382137 ISBN 13: 9780792382133

Casa editrice: SPRINGER NATURE, 1998

Riassunto

This overview of iterative learning control theory and techniques is relevant to industrial automation, and focuses on research directions for the 21st century. It examines the important aspects of this emerging technology, and provides 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 problems, 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. This volume should be of interest to researchers and engineers in robotics, automation, systems and control, and signal processing.

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Contenuti

List of Figures. List of Tables. Preface. Part I: General Introduction to Iterative Learning Control. 1. A Brief History of Iterative Learning Control; S. Arimoto. 2. The Frontiers of Iterative Learning Control; Jian-Xin Xu, Zenn Z. Bien. Part II: Property Analysis of Iterative Learning Control. 3. Robustness and Convergence of a PD-type Iterative Learning Controller; Hak-Sung Lee, Zeungnam Bien. 4. Ability of Learning Comes from Passivity and Dissipativity of System Dynamics; S. Arimoto. 5. On the Iterative Learning Control of Sampled-Data Systems; Chiang-Ju Chien. 6. High-Order Iterative Learning Control of Discrete-Time Nonlinear Systems Using Current Iteration Tracking Error; Yangquan Chen, et al. Part III: The Design Issues of Iterative Learning Control. 7. Designing Iterative Learning and Repetitive Controllers; R.W. Longman. 8. Design of an ILC for Linear Systems with Time-Delay and Initial State Error; Kwang-Hyun Park, et al. 9. Design of Quadratic Criterion-Based Iterative Learning Control; Kwang Soon Lee, J.H. Lee. 10. Robust ILC with Current Feedback for Uncertain Linear Systems; Tae-Yong Doh, Myung Jin Chung. Part IV: Integration of Iterative Learning Control with Other Intelligent Controls. 11. Model Reference Learning Control with a Wavelet Network; M. Fukuda, S. Shin. 12. Neural-Based Iterative Learning Control; Jin Young Choi, et al. 13. Adaptive Learning Control of Robotic Systems and Its Extension to a Class of Nonlinear Systems; B.H. Park, et al. 14. Direct Learning Control of Non-Uniform Trajectories; Jian-Xin Xu, Yanbin Song. 15. System Identification and Learning Control; M.Q. Phan, J.A. Frueh. Part V: Implementations of Iterative Learning Control Method. 16. Model-Based Predictive Control Combined with Iterative Learning for Batch or Repetitive Processes; Kwang Soon Lee, J.H. Lee. 17. Iterative Learning Control with Non-Standard Assumptions Applied to the Control of Gas-Metal Arc Welding; K.L. Moore, A. Matheus. 18. Robust Control of Functional Neuromuscular Stimulation System by Discrete-time Iterative Learning; Huifang Dou, et al. Index. About the Editors.

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Dettagli dell'edizione

• Editore: SPRINGER NATURE
• Data di pubblicazione: 1998
• Lingua: Inglese
• ISBN 10: 0792382137
• ISBN 13: 9780792382133
• Rilegatura: Copertina rigida
• Numero di pagine: 373
• Redattore: Bien Zeungnam, Jian-Xin Xu
• Contatto del produttore: non disponibile
• Persona responsabile: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania