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04328nam a22005895i 4500 |
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978-1-84882-175-0 |
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DE-He213 |
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20151204142029.0 |
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cr nn 008mamaa |
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100301s2009 xxk| s |||| 0|eng d |
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|a 9781848821750
|9 978-1-84882-175-0
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|a 10.1007/978-1-84882-175-0
|2 doi
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|a 629.8
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|a Xu, Jian-Xin.
|e author.
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|a Real-time Iterative Learning Control
|h [electronic resource] :
|b Design and Applications /
|c by Jian-Xin Xu, Sanjib K. Panda, Tong Heng Lee.
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| 264 |
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|a London :
|b Springer London,
|c 2009.
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| 300 |
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|a XVI, 194 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Advances in Industrial Control,
|x 1430-9491
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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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|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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|a Engineering.
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|a Chemical engineering.
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|a Engineering design.
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|a Control engineering.
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|a Manufacturing industries.
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|a Machines.
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|a Tools.
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|a Electronics.
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|a Microelectronics.
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|a Engineering.
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|a Control.
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| 650 |
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|a Industrial Chemistry/Chemical Engineering.
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|a Manufacturing, Machines, Tools.
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|a Engineering Design.
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| 650 |
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|a Electronics and Microelectronics, Instrumentation.
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| 700 |
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|a Panda, Sanjib K.
|e author.
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| 700 |
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|a Lee, Tong Heng.
|e author.
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| 710 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9781848821743
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| 830 |
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|a Advances in Industrial Control,
|x 1430-9491
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/978-1-84882-175-0
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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