LEADER 03315nam 22005413 450 001 9911018967103321 005 20240321080236.0 010 $a9781119471424 010 $a1119471427 010 $a9781119471455 010 $a1119471451 035 $a(MiAaPQ)EBC31214543 035 $a(Au-PeEL)EBL31214543 035 $a(Exl-AI)31214543 035 $a(CKB)30967970100041 035 $a(OCoLC)1427664730 035 $a(EXLCZ)9930967970100041 100 $a20240321d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModel Predictive Control 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2024. 210 4$dİ2024. 215 $a1 online resource (307 pages) 225 1 $aIEEE Press Series 311 08$a9781119471394 311 08$a1119471397 327 $aCover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- Acronyms -- Introduction -- Chapter 1 Concepts -- 1.1 PID and Model Predictive Control -- 1.2 Two?Layered Model Predictive Control -- 1.3 Hierarchical Model Predictive Control -- Chapter 2 Parameter Estimation and Output Prediction -- 2.1 Test Signal for Model Identification -- 2.1.1 Step Test -- 2.1.2 White Noise -- 2.1.3 Pseudo?Random Binary Sequence -- 2.1.4 Generalized Binary Noise -- 2.2 Step Response Model Identification -- 2.2.1 Model -- 2.2.2 Data Processing -- 2.2.2.1 Marking or Interpolation of Bad Data -- 2.2.2.2 Smoothing Data -- 2.2.3 Model Identification -- 2.2.3.1 Case Grouping -- 2.2.3.2 Cased Data Preparation for Stable Dependent Variables -- 2.2.3.3 Cased Data Preparation for Integral Dependent Variables -- 2.2.3.4 Least Square Solution to Parameter Regression -- 2.2.3.5 Least Square Solution by SVD Decomposition -- 2.2.3.6 Filtering Pulse Response Coefficients$7Generated by AI. 330 $aThis book provides an in-depth exploration of Model Predictive Control (MPC), a class of model-based control algorithms. It delves into various aspects such as parameter estimation, steady-state target calculation, and two-layered dynamic matrix control (DMC) for stable and integral processes. The authors, Baocang Ding and Yuanqing Yang, aim to educate both undergraduate and graduate students, as well as practitioners in automation and control systems. The text covers theoretical foundations and practical applications, including robust and heuristic models, output feedback, and real-time optimization. The book is intended for those studying or working in fields like process control and automation, offering insights into advanced control strategies and algorithm implementation.$7Generated by AI. 410 0$aIEEE Press Series 606 $aPredictive control$7Generated by AI 606 $aProcess control$7Generated by AI 615 0$aPredictive control 615 0$aProcess control 676 $a629.8 700 $aDing$b Baocang$01758050 701 $aYang$b Yuanqing$01758051 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911018967103321 996 $aModel Predictive Control$94196116 997 $aUNINA