000 04475nam a22006135i 4500
001 978-1-84628-829-6
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008 100301s2007 xxk| s |||| 0|eng d
020 _a9781846288296
_9978-1-84628-829-6
024 7 _a10.1007/978-1-84628-829-6
_2doi
050 4 _aTJ210.2-211.495
050 4 _aT59.5
072 7 _aTJFM1
_2bicssc
072 7 _aTEC037000
_2bisacsh
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.892
_223
100 1 _aNormey-Rico, J. E.
_eauthor.
245 1 0 _aControl of Dead-time Processes
_h[electronic resource] /
_cby J. E. Normey-Rico, E. F. Camacho.
264 1 _aLondon :
_bSpringer London,
_c2007.
300 _aXXV, 462 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvanced Textbooks in Control and Signal Processing,
_x1439-2232
505 0 _aDead-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.
520 _aIndustrial 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.
650 0 _aEngineering.
650 0 _aChemical engineering.
650 0 _aSystem theory.
650 0 _aControl engineering.
650 0 _aRobotics.
650 0 _aAutomation.
650 0 _aIndustrial engineering.
650 0 _aProduction engineering.
650 0 _aElectrical engineering.
650 1 4 _aEngineering.
650 2 4 _aRobotics and Automation.
650 2 4 _aControl.
650 2 4 _aIndustrial Chemistry/Chemical Engineering.
650 2 4 _aIndustrial and Production Engineering.
650 2 4 _aSystems Theory, Control.
650 2 4 _aElectrical Engineering.
700 1 _aCamacho, E. F.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781846288289
830 0 _aAdvanced Textbooks in Control and Signal Processing,
_x1439-2232
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-84628-829-6
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c509679
_d509679