| 强流束晕-混沌的RBF神经网络控制 |
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| 引用本文： | 高远,袁海英,孔峰,谭光兴. 强流束晕-混沌的RBF神经网络控制[J]. 宁夏大学学报(自然科学版), 2011, 0(3): 231-234 |
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| 作者姓名： | 高远 袁海英 孔峰 谭光兴 |
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| 作者单位： | 广西工学院电子信息与控制工程系 |
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| 基金项目： | 广西自然科学基金资助项目(2010GXNSFA013126);广西教育厅科研资助项目(201010LX243) |
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| 摘 要： | 以周期性聚焦磁场通道中的Kapchinskij-Vladimirskij（K-V）分布离子束为对象,研究了强流束晕-混沌现象的RBFNN自适应控制方法.该方法以神经网络的输出作为周期聚焦磁场的线性控制因子,通过对外部磁场的线性调节实现束晕-混沌控制.模拟结果表明：当选择恰当的RBFNN控制结构,自适应调整其内部参数,可将混沌变化的束包络半径控制在匹配半径附近单周期稳定振荡;该方法用于多粒子模拟系统中,能较好改善束的品质,束晕-混沌现象能得到有效抑制.
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| 关 键 词： | 强流离子束 束晕-混沌 混沌控制 RBF神经网络控制 |
Control of High-current Beam Halo-chaos Based on RBF Neural Network |
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| Gao Yuan,Yuan Haiying,Kong Feng,Tan Guangxing. Control of High-current Beam Halo-chaos Based on RBF Neural Network[J]. Journal of Ningxia University(Natural Science Edition), 2011, 0(3): 231-234 |
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| Authors: | Gao Yuan Yuan Haiying Kong Feng Tan Guangxing |
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| Affiliation: | (Department of Electronic Information and Control Engineering,Guangxi University of Technology,Liuzhou 545006,China) |
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| Abstract: | The Kapchinskij-Vladimirskij（K-V） distribution beam in the periodical focusing channels（PFCS） is selected as typical example,and a control method based on radial basis function neural network（RBFNN） is presented for control beam halo-chaos.The output of network as a controlling element is used to adjust focusing magnetic filed proportionally for control beam halo-chaos.Numerical results show that chaotic envelope radius of high-current beam can be controlled efficiently to the neighborhood of matched radius.This method is also applied to the multi-particle model.Under the control condition,the beam halos can be suppressed effectively,and quality of ion beam is improved evidently.This method provides a useful reference for controlling beam halo-chaos of high current beam in the PFCs. |
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| Keywords: | high-current ion beam beam halo-chaos chaos control RBF neural network control |
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