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130626 ||| eng |
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|a 9781848821750
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| 100 |
1 |
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|a Xu, Jian-Xin
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| 245 |
0 |
0 |
|a Real-time Iterative Learning Control
|h Elektronische Ressource
|b Design and Applications
|c by Jian-Xin Xu, Sanjib K. Panda, Tong Heng Lee
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| 250 |
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|a 1st ed. 2009
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| 260 |
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|a London
|b Springer London
|c 2009, 2009
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| 300 |
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|a XVI, 194 p
|b online resource
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| 505 |
0 |
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|a to ILC: Concepts, Schematics, and Implementation -- Robust Optimal ILC Design for Precision Servo: Application to an XY Table -- ILC for Precision Servo with Input Non-linearities: Application to a Piezo Actuator -- ILC for Process Temperature Control: Application to a Water-heating Plant -- ILC with Robust Smith Compensator: Application to a Furnace Reactor -- Plug-in ILC Design for Electrical Drives: Application to a PM Synchronous Motor -- ILC for Electrical Drives: Application to a Switched Reluctance Motor -- Optimal Tuning of PID Controllers Using Iterative Learning Approach -- Calibration of Micro-robot Inverse Kinematics Using Iterative Learning Approach -- Conclusion
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| 653 |
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|a Control engineering
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| 653 |
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|a Electronics and Microelectronics, Instrumentation
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| 653 |
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|a Electronics
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| 653 |
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|a Chemistry, Technical
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| 653 |
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|a Control and Systems Theory
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| 653 |
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|a Manufactures
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| 653 |
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|a Industrial Chemistry
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| 653 |
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|a Engineering Design
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| 653 |
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|a Engineering design
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| 653 |
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|a Machines, Tools, Processes
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| 700 |
1 |
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|a Panda, Sanjib K.
|e [author]
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| 700 |
1 |
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|a Lee, Tong Heng
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Advances in Industrial Control
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| 028 |
5 |
0 |
|a 10.1007/978-1-84882-175-0
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| 856 |
4 |
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|u https://doi.org/10.1007/978-1-84882-175-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 003
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| 082 |
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|a 629.8312
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| 520 |
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|a 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, characterised 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 hitherto lacking systematic introduction to real-time ILC design and 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. In particular, the book discusses: • ILC design in the continuous- and discrete-time domains; • design in the frequency and time domains; • design with problem-specific performance objectives including robustness and optimality; • design by means of classical tools based on Bode plots and state space; and • iterative-learning-based parametric identification. Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.
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