TY - CHAP A1 - Michail Petrov A2 - Sevil Ahmed A3 - Alexander Ichtev A4 - Albena Taneva ED1 - Tao Zheng Y1 - 2011-07-05 PY - 2011 T1 - Fuzzy–neural Model Predictive Control of Multivariable Processes 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. 7 UR - https://doi.org/10.5772/16828 DO - 10.5772/16828 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-06-15 ER -