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应用科学学报 ›› 2004, Vol. 22 ›› Issue (3): 388-391.

• 论文 • 上一篇    下一篇

基于RBF神经网络的免疫控制器结构

张正道1,2, 胡寿松1   

  1. 1 南京航空航天大学自动化学院 江苏南京 210016;
    2 江南大学通信与控制工程学院 江苏无锡 214036
  • 收稿日期:2003-04-17 修回日期:2003-08-28 出版日期:2004-09-30 发布日期:2004-09-30
  • 作者简介:张正道(1976-),男,江苏无锡人,讲师,博士生;胡寿松(1937-),男,江苏南京人,教授,博导.
  • 基金资助:
    国家自然科学基金重点资助项目(60234010)

The Structure of the Immunocontroller Based on RBF Neural Networks

ZHANG Zheng-dao1,2, HU Shou-song1   

  1. 1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    2. School of Communication & Control Engineering, Southern Yangtze University, Wuxi 214036, China
  • Received:2003-04-17 Revised:2003-08-28 Online:2004-09-30 Published:2004-09-30

PDF

73

被引次数

4

摘要： 从T细胞介导的免疫过程出发,通过对其数学模型的简化,利用RBF神经网络构造了一种基于生物系统免疫反馈机理的控制器.该控制器以正反馈模拟免疫激励,提高了系统的快速性;以负反馈模拟免疫抑制,增强了系统的稳定性和鲁棒性.文中对于一类仿射非线性系统证明了其作为控制器时的系统闭环稳定性.仿真实验表明,该控制器对系统的噪声具有很好的抑制能力.

关键词: 免疫, 免疫反馈, 鲁棒性, RBF神经网络, 免疫控制器

Abstract: Basing on the course of immunity mediated by T lymphocyte, we have constructed a new controller structure based on the immune feedback mechansim of biological immune systems by simplifying the mathematical model of the immune mediated by Tlymphocyte and using the RBF neural network. We used positive feedback to simulate the process of immunologic enhancement for improving the speediness of the system and used negative feedback to simulate the process of immunological suppression for improving the stability and robustness. As a feed-forward controlled of a kind of affine nonlinear systems, the stability was proved in this paper. Computer simulation results demonstrated that the suppression ability of the controller against the system's noise is satisfactory.

Key words: immune, immunocontroller, immune feedback, robustness, RBF neural networks

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