000 06494cam a22006378i 4500
001 on1084630879
003 OCoLC
005 20220711203502.0
006 m o d
007 cr |||||||||||
008 190204s2019 nju ob 001 0 eng
010 _a 2019005389
040 _aDLC
_beng
_erda
_cDLC
_dOCLCO
_dOCLCF
_dN$T
_dEBLCP
_dRECBK
_dDG1
_dUKAHL
020 _a1119119588
020 _a9781119119579
_q(ePub)
020 _a111911957X
_q(ePub)
020 _a9781119119593
_q(electronic bk. : oBook)
020 _a1119119596
_q(electronic bk. : oBook)
020 _a9781119119586
_q(electronic bk.)
020 _z9781119119548 (hardback)
029 1 _aAU@
_b000065535784
029 1 _aCHVBK
_b571898564
029 1 _aCHNEW
_b001060488
035 _a(OCoLC)1084630879
042 _apcc
050 1 0 _aTJ217.6
082 0 0 _a629.8
_223
049 _aMAIN
100 1 _aXi, Yugeng,
_d1946-
_eauthor.
_98124
245 1 0 _aPredictive control :
_bfundamentals and developments /
_cYugeng Xi, Shanghai Jiao Tong University, Shanghai, China, Dewei Li, Shanghai Jiao Tong University, Shanghai, China.
250 _aFirst edition.
263 _a1907
264 1 _aHoboken, NJ :
_bJohn Wiley & Sons, Inc.,
_c[2019]
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bn
_2rdamedia
338 _aonline resource
_bnc
_2rdacarrier
504 _aIncludes bibliographical references and index.
520 _a"Systematically introduces fundamental concepts, basic algorithms, and applications of MPC -Includes a comprehensive overview of MPC development, emphasizing recent advances and modern approaches - Features numerous MPC models and structures, based on rigorous research -Based on the best-selling Chinese edition, which has become a cornerstone in the Chinese market Modeling Predictive Control (MPC) is an advanced control technology that can effectively handle optimization control under constraints. Since MPC appeared in the industrial process control field in the 1970's, the demand for constrained optimization control, in particular MPC, in various application fields has been increasing continuously. The MPC application fields extend from traditional oil refinery, petrochemical, and chemical industries, to almost all fields such as power systems, manufacturing, aerospace, electromechanics, urban transportation, agricultural greenhouse, and medicine etc. MPC has the ability to anticipate future events and can take control actions accordingly. PID and LQR controllers do not have this predictive ability. MPC is nearly universally implemented as a digital control, although there is research into achieving faster response times with specially designed analog circuitry"--
_cProvided by publisher.
588 _aDescription based on print version record and CIP data provided by publisher; resource not viewed.
505 0 _aIntro; Title Page; Copyright Page; Contents; Preface; Chapter 1 Brief History and Basic Principles of Predictive Control; 1.1 Generation and Development of Predictive Control; 1.2 Basic Methodological Principles of Predictive Control; 1.2.1 Prediction Model; 1.2.2 Rolling Optimization; 1.2.3 Feedback Correction; 1.3 Contents of this Book; References; Chapter 2 Some Basic Predictive Control Algorithms; 2.1 Dynamic Matrix Control (DMC) Based on the Step Response Model; 2.1.1 DMC Algorithm and Implementation; 2.1.2 Description of DMC in the State Space Framework
505 8 _a2.2 Generalized Predictive Control (GPC) Based on the Linear Difference Equation Model2.3 Predictive Control Based on the State Space Model; 2.4 Summary; References; Chapter 3 Trend Analysis and Tuning of SISO Unconstrained DMC Systems; 3.1 The Internal Model Control Structure of the DMC Algorithm; 3.2 Controller of DMC in the IMC Structure; 3.2.1 Stability of the Controller; 3.2.2 Controller with the One-Step Optimization Strategy; 3.2.3 Controller for Systems with Time Delay; 3.3 Filter of DMC in the IMC Structure; 3.3.1 Three Feedback Correction Strategies and Corresponding Filters
505 8 _a3.3.2 Influence of the Filter to Robust Stability of the System3.4 DMC Parameter Tuning Based on Trend Analysis; 3.5 Summary; References; Chapter 4 Quantitative Analysis of SISO Unconstrained Predictive Control Systems; 4.1 Time Domain Analysis Based on the Kleinman Controller; 4.2 Coefficient Mapping of Predictive Control Systems; 4.2.1 Controller of GPC in the IMC Structure; 4.2.2 Minimal Form of the DMC Controller and Uniform Coefficient Mapping; 4.3 Z Domain Analysis Based on Coefficient Mapping; 4.3.1 Zero Coefficient Condition and the Deadbeat Property of Predictive Control Systems
505 8 _a4.3.2 Reduced Order Property and Stability of Predictive Control Systems4.4 Quantitative Analysis of Predictive Control for Some Typical Systems; 4.4.1 Quantitative Analysis for First-Order Systems; 4.4.2 Quantitative Analysis for Second-Order Systems; 4.5 Summary; References; Chapter 5 Predictive Control for MIMO Constrained Systems; 5.1 Unconstrained DMC for Multivariable Systems; 5.2 Constrained DMC for Multivariable Systems; 5.2.1 Formulation of the Constrained Optimization Problem in Multivariable DMC; 5.2.2 Constrained Optimization Algorithm Based on the Matrix Tearing Technique
505 8 _a5.2.3 Constrained Optimization Algorithm Based on QP5.3 Decomposition of Online Optimization for Multivariable Predictive Control; 5.3.1 Hierarchical Predictive Control Based on Decomposition-Coordination; 5.3.2 Distributed Predictive Control; 5.3.3 Decentralized Predictive Control; 5.3.4 Comparison of Three Decomposition Algorithms; 5.4 Summary; References; Chapter 6 Synthesis of Stable Predictive Controllers; 6.1 Fundamental Philosophy of the Qualitative Synthesis Theory of Predictive Control; 6.1.1 Relationships between MPC and Optimal Control
650 0 _aPredictive control.
_98125
650 7 _aTECHNOLOGY & ENGINEERING / Engineering (General).
_2bisacsh
_98126
650 7 _aPredictive control.
_2fast
_0(OCoLC)fst01075040
_98125
655 0 _aElectronic books.
_93294
655 4 _aElectronic books.
_93294
700 1 _aLi, Dewei
_c(Computer scientist),
_eauthor.
_98127
776 0 8 _iPrint version:
_aXi, Yugeng, 1946- author.
_tPredictive control
_bFirst edition.
_dHoboken, NJ : John Wiley & Sons, Inc., [2019]
_z9781119119548
_w(DLC) 2019003713
856 4 0 _uhttps://doi.org/10.1002/9781119119593
_zWiley Online Library
942 _cEBK
994 _a92
_bDG1
999 _c69024
_d69024