Neural network nonlinear predictive control based on tent-map chaos optimization

作者：Song Ying; Chen Zengqiang^*; Yuan Zhuzhi

来源：Chinese Journal of Chemical Engineering, 2007, 15(4): 539-544.

DOI：10.1016/S1004-9541(07)60121-9

• model-based predictive control
• neural network
• Tent-map
• chaos optimization
• nonlinear system

With the unique ergodicity, irregularity, and special ability to avoid being trapped in local optima, chaos optimization has been a novel global optimization technique and has attracted considerable attention for application in various fields, such as nonlinear programming problems. In this article, a novel neural network nonlinear predictive control (NNPC) strategy based on the new Tent-map chaos optimization algorithm (TCOA) is presented. The feedforward neural network is used as the multi-step predictive model. In addition, the TCOA is applied to perform the nonlinear rolling optimization to enhance the convergence and accuracy in the NNPC. Simulation on a laboratory-scale liquid-level system is given to illustrate the effectiveness of the proposed method.

• 出版日期2007-8
• 单位南开大学