| QDPSO滚动优化的LS-SVM预测控制研究 |
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| 引用本文： | 张天瑜. QDPSO滚动优化的LS-SVM预测控制研究[J]. 武汉理工大学学报, 2010, 0(3) |
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| 作者姓名： | 张天瑜 |
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| 作者单位： | 无锡市广播电视大学机电工程系; |
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| 摘 要： | 针对非线性强时滞系统,传统的预测控制算法难以建立精确模型,其控制精度不高。提出一种基于最小二乘支持向量机(LS-SVM)的非线性模型预测控制算法,该算法通过LS-SVM对非线性系统输入输出数据序列的训练学习,构建其离线的预测模型,然后运用量子粒子群优化(QDPSO)算法来完成整个滚动优化的过程。仿真结果表明基于LS-SVM的非线性模型预测控制比动态矩阵控制具有更好的控制品质。
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| 关 键 词： | 非线性模型预测控制 最小二乘支持向量机 核函数 量子粒子群优化算法 滚动优化 动态矩阵控制 |
Research on LS-SVM Predictive Controlling Using QDPSO Rolling Optimization |
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| ZHANG Tian-yu. Research on LS-SVM Predictive Controlling Using QDPSO Rolling Optimization[J]. Journal of Wuhan University of Technology, 2010, 0(3) |
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| Authors: | ZHANG Tian-yu |
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| Affiliation: | ZHANG Tian-yu(Department of Mechanical , Electrical Engineering,Wuxi Radio & Television University,Wuxi 214011,China) |
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| Abstract: | It is difficult to build an accurate model by using traditional predictive control algorithm for the nonlinear system of strong time delay.So its control accuracy is not high.A nonlinear model predictive control(NMPC) algorithm based on least squares support vector machine(LS-SVM) is proposed.The off-line predictive model of nonlinear system is established by LS-SVM to train a sequence data of input and output.Then the whole rolling optimization procedure is finished by the algorithm of quantum delta-potent... |
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| Keywords: | nonlinear model predictive control least squares support vector machine kernal function QDPSO algorithm rolling optimization dynamic matrix control |
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