TY - CHAP A1 - Luis Alberto Paz Suarez A2 - Petia Georgieva A3 - Sebastiao Feyo de Azevedo ED1 - Tao Zheng Y1 - 2011-07-05 PY - 2011 T1 - Model Predictive Control Strategies for Batch Sugar Crystallization Process N2 - Model 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. BT - Advanced Model Predictive Control SP - Ch. 11 UR - https://doi.org/10.5772/16853 DO - 10.5772/16853 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-06-16 ER -