| 基于Tent混沌优化的神经网络预测控制 |
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| 引用本文： | 宋莹,陈增强,袁著祉.基于Tent混沌优化的神经网络预测控制[J].中国化学工程学报,2007,15(4):539-544. |
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| 作者姓名： | 宋莹 陈增强 袁著祉 |
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| 作者单位： | Department of Automation Nankai University，Department of Automation，Nankai University，Department of Automation，Nankai University，Tianjin 300071，China，Tianjin 300071，China，Tianjin 300071，China |
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| 基金项目： | Supported by the National Natural Science Foundation of China （No.60374037, No.60574036）, the Program for New Century Excellent Talents in University of China （NCET）, the Specialized Research Fund for the Doctoral Program of Higher Education of China （No.20050055013）, .and the 0pening Project Foundation of National Lab of Industrial Control Technology （No.0708008）. |
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| 摘 要： | With the unique erggdicity, i rregularity, 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 predic-tive control （NNPC） strategy baseed on the new Tent-map chaos optimization algorithm （TCOA） is presented. Thefeedforward 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 labora-tory-scale liquid-level system is given to illustrate the effectiveness of the proposed method.
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| 关 键 词： | 神经中枢网络 基础模型预言控制 混沌最优化 非线性系统 |
| 收稿时间： | 4 September 2006 |
| 修稿时间： | 2006-09-04 |
Neural Network Nonlinear Predictive Control Based on Tent-map Chaos Optimization |
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| Ying SONG, Zengqiang CHEN,Zhuzhi YUAN.Neural Network Nonlinear Predictive Control Based on Tent-map Chaos Optimization[J].Chinese Journal of Chemical Engineering,2007,15(4):539-544. |
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| Authors: | Ying SONG Zengqiang CHEN Zhuzhi YUAN |
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| Affiliation: | Department of Automation, Nankai University, Tianjin 300071, China |
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| Abstract: | 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 predic- tive 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 labora- tory-scale liquid-level system is given to illustrate the effectiveness of the proposed method. |
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| Keywords: | model-based predictive control neural network Tent-map chaos optimization nonlinear system |
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