| 000 | 01744nam a2200241 a 4500 | ||
|---|---|---|---|
| 001 | vtls000085805 | ||
| 003 | KUKTEM | ||
| 005 | 20251125103043.0 | ||
| 008 | 150416t2011 ci a f 000 0 eng d | ||
| 020 | _a9789533072982 | ||
| 020 | _a9533072989 | ||
| 039 | 9 |
_a201508281120 _basma _c201508281119 _dasma _c201508281119 _dasma _y201504161621 _zezzatul |
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| 040 | _aUMP | ||
| 090 | _aTJ217.6 .A38 2011 | ||
| 245 | 0 | 0 |
_aAdvanced model predictive control / _cedited by Tao Zheng |
| 260 |
_aCroatia : _bINTECH, _c2011 |
||
| 300 |
_ax, 418 p. : _bill. ; _c26 cm. |
||
| 504 | _aIncludes bibliographical references | ||
| 520 | _aModel Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in this area. The first part of this exciting book will help you comprehend the frontiers in theoretical research of MPC, such as Fast MPC, Nonlinear MPC, Distributed MPC, Multi-Dimensional MPC and Fuzzy-Neural MPC. In the second part, several excellent applications of MPC in modern industry are proposed and efficient commercial software for MPC is introduced. Because of its special industrial origin, we believe that MPC will remain energetic in the future | ||
| 650 | 0 | _aPredictive control | |
| 700 | 1 | _aZheng, Tao | |
| 999 |
_aVIRTUA40 _c81816 _d81822 |
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| 999 | _aVTLSSORT0080*0200*0201*0400*0900*2450*2600*3000*5040*5200*6500*7000*9992 | ||