000 04070nam a22005415i 4500
001 978-3-642-03193-9
003 DE-He213
005 20170628035055.0
007 cr nn 008mamaa
008 100301s2009 gw | s |||| 0|eng d
020 _a9783642031939
_9978-3-642-03193-9
024 7 _a10.1007/978-3-642-03193-9
_2doi
050 4 _aTJ210.2-211.495
050 4 _aTJ163.12
072 7 _aTJFM
_2bicssc
072 7 _aTJFD
_2bicssc
072 7 _aTEC004000
_2bisacsh
072 7 _aTEC037000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aKhaki-Sedigh, Ali.
_eauthor.
245 1 0 _aControl Configuration Selection for Multivariable Plants
_h[electronic resource] /
_cby Ali Khaki-Sedigh, Bijan Moaveni.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2009.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Control and Information Sciences,
_x0170-8643 ;
_v391
505 0 _aControl Configuration Selection of Linear Multivariable Plants: The RGA Approach -- Control Configuration of Linear Multivariable Plants: Advanced RGA Based Techniques -- Control Configuration Selection of Linear Multivariable Plants: SSV and Passivity Based Techniques -- Control Configuration Selection of Linear Multivariable Plants Based on the State-Space Models -- Control Configuration Selection of Nonlinear Multivariable Plants -- Control Configuration Selection of Linear Uncertain Multivariable Plants -- Appendix: Mathematical Models Used in Examples.
520 _aControl of multivariable industrial plants and processes has been a challenging and fascinating task for researchers in this field. The analysis and design methodologies for multivariable plants can be categorized as centralized and decentralized design strategies. Despite the remarkable theoretical achievements in centralized multiva- able control, decentralized control is still widely used in many industrial plants. This trend in the beginning of the third millennium is still there and it will be with us for the foreseeable future. This is mainly because of the easy implementation, main- nance, tuning, and robust behavior in the face of fault and model uncertainties, which is reported with the vast number of running decentralized controllers in the industry. The main steps involved in employing decentralized controllers can be summarized as follows: • Control objectives formulation and plant modeling. • Control structure selection. • Controller design. • Simulation or pilot plant experiments and Implementation. Nearly all the textbooks on multivariable control theory deal only with the control system analysis and design. The important concept of control structure selection which is a key prerequisite for a successful industrial control strategy is almost unnoticed. Structure selection involves the following two main steps: • Inputs and outputs selection. • Control configuration selection or the input-output pairing problem. This book focuses on control configuration selection or the input-output pairing problem, which is defined as the procedure of selecting the appropriate input and output pair for the design of SISO (or block) controllers.
650 0 _aEngineering.
650 0 _aSystems theory.
650 0 _aMechanical engineering.
650 0 _aIndustrial engineering.
650 1 4 _aEngineering.
650 2 4 _aControl, Robotics, Mechatronics.
650 2 4 _aSystems Theory, Control.
650 2 4 _aIndustrial and Production Engineering.
650 2 4 _aMechanical Engineering.
700 1 _aMoaveni, Bijan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642031922
830 0 _aLecture Notes in Control and Information Sciences,
_x0170-8643 ;
_v391
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-03193-9
912 _aZDB-2-ENG
999 _c22850
_d22850