Academic Editor: Irina N. Trendafilova
Copyright © 2010 Wang Ya-feng et al. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The model predictive control (MPC) subject to control and state constraint is studied. Given a terminal cost, a terminal region is obtained through iterative estimation by using support vector machine (SVM). It is proved that the obtained terminal region is the largest terminal region when the terminal cost is given. The relationships between terminal cost and terminal region and between terminal cost and total cost are discussed, respectively. Based on these relationships, a simple method to get a suitable terminal cost is proposed and it can be adjusted according to our need. Finally, some experiment results are presented.