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04492nam a22006135i 4500 |
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|a 9781846288296
|9 978-1-84628-829-6
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|a 10.1007/978-1-84628-829-6
|2 doi
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|a TJ210.2-211.495
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|a 629.892
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|a Normey-Rico, J. E.
|e author.
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|a Control of Dead-time Processes
|h [electronic resource] /
|c by J. E. Normey-Rico, E. F. Camacho.
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|a London :
|b Springer London,
|c 2007.
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|a XXV, 462 p.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Advanced Textbooks in Control and Signal Processing,
|x 1439-2232
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|a Dead-time Processes -- Identification of Dead-time Processes -- PID Control of Dead-time Processes -- The Smith Predictor -- Dead-time Compensators for Stable Plants -- Dead-time Compensators for Unstable Plants -- Discrete Dead-time Compensators -- Model Predictive Control of Dead-time Processes -- Robust Predictive Control of Dead-time Processes -- Multivariable Dead-time Compensation -- Robust MPC for MIMO Dead-time Processes -- Control of Nonlinear Dead-time Processes -- Prediction for Control.
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|a Industrial processes and engineering, economic and biological systems commonly exhibit time delays or dead times. Dead time complicates the analysis and design of control systems and makes satisfactory control more difficult. Control of Dead-time Processes introduces the fundamental techniques for controlling dead-time processes ranging from simple monovariable to complex multivariable cases. Solutions to dead-time-process-control problems are studied using classical proportional-integral-differential (PID) control for the simpler examples and dead-time-compensator (DTC) and model predictive control (MPC) methods for progressively more complex ones. Although MPC and DTC approaches originate in different areas of control, both use predictors to overcome the effects of dead time. Using this fact, the text analyses MPC as a dead-time-compensation strategy and shows how it can be used synergistically with robust DTC tuning methodologies. Graduate students working for their masters or PhDs in automatic control, chemical, electronic or mechanical engineering, in which dead-time processes are prevalent, will gain particular benefit from the following features of this text: • interlinked study of PID, DTC and MPC for dead-time processes in a single source; • exercises and further reading for each chapter; • extensive use of illustrations, tables and examples; • case studies based on real industrial problems with solutions that are simple to understand and easy to implement; • MATLAB® code developed by the authors to help analyse and control dead-time processes including code for all the examples in the book available for download from www.das.ufsc.br/~julio/deadtimebook and www.esi2.us.es/~eduardo/deadtimebook. Control of Dead-time Processes will also be of interest to control researchers and process control engineers. Chapters 1-8 of the text can be used as part of the final-year course for undergraduates in control or process engineering.
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|a Engineering.
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|a Chemical engineering.
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|a System theory.
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|a Control engineering.
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|a Robotics.
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|a Automation.
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|a Industrial engineering.
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|a Production engineering.
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|a Electrical engineering.
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|a Robotics and Automation.
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|a Control.
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|a Industrial Chemistry/Chemical Engineering.
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|a Industrial and Production Engineering.
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|a Systems Theory, Control.
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|a Electrical Engineering.
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|a Camacho, E. F.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9781846288289
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|a Advanced Textbooks in Control and Signal Processing,
|x 1439-2232
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|u http://dx.doi.org/10.1007/978-1-84628-829-6
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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|a Engineering (Springer-11647)
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