期刊文献+

基于FLANN的非线性动态系统辨识 被引量:2

Nonlinear Dynamic System Identification Based on FLANN
在线阅读 下载PDF
导出
摘要 采用一种基于FLANN-PSO的SISO非线性动态系统辨识方法,构造了基于FLANN的辨识模型,然后运用PSO优化算法实现模型权值辨识.通过对4种典型非线性动态系统进行了辨识仿真,结果表明该方法具有良好的性能和高辨识精度,它将更适合于工程实际需要. A method of SISO Nonlinear Dynamic System Identification was proposed based on FLANN-PSO.At first,identification model based on FLANN was constructed,and then its weights were calculated by PSO optimization algorithm.The simulation result of four models for nonlinear dynamic systems showed that the method had excellent identification performance and accuracy,and thus it would be more applicable to the engineering practice.
作者 王荣杰 朱昱
出处 《集美大学学报(自然科学版)》 CAS 2011年第2期128-134,共7页 Journal of Jimei University:Natural Science
基金 广东省科技项目(2009390004202223)
关键词 非线性 动态 系统辨识 FLANN PSO优化算法 nonlinear dynamic system identification FLANN PSO optimization algorithm
  • 相关文献

参考文献14

  • 1NARENDRA K S, PARTHASARATHY K. Identification and control of dynamical systems using neural networks [ J ]. IEEE Transactions on Neural Networks, 1990, 1 ( 1 ) : 4-27.
  • 2PURWAR S, KARI N, JHA A N. On-line system idetification of complex systems using chebyshev neural networks [ J]. Applied Soft Computing, 2007,7 (1) : 364-372.
  • 3GUPTA M M, JIN L, HOMMA N. Static and dynamic neural networks: from fundamentals to advanced theory [ M]. New York: Wiley Interscience, 2003.
  • 4ANTSAKLIS P J. Neural networks in control systems [J]. IEEE Control Syst Mag, 1990, 1(2) : 3-5.
  • 5PARLOS A G, CHONG K T, ATIYA A F. Application of recurrent muhilayer perceptron in modeling of complex process dynamics [ J ]. IEEE Transactions on Neural Networks, 1994, 5 (2) : 255-266.
  • 6POGGIOT, GIROSI F. Networks for approximation and learning [ J ]. Proceeding of IEEE, 1990, 78 (9) : 1481-1497.
  • 7CHEN S, BILLINGS S A, GRANT P M. Recursive hybrid algorithm for nonlinear system identification using radial basis function networks [ J]. International Journal of Control, 1992, 55 (5) : 1051-1070.
  • 8PARK J, SANDBERG I W. Universal approximation sing radial basis function networks [ J ]. Neural Computation, 1991,3(2) : 246-257.
  • 9NGUYEN D H, WIDROW B. Neural networks for self-learning control system [ J ]. International Journal of Control, 1991,54(6) : 1439-1451.
  • 10GEMBRANO G, WELLS G, SARDA J. Dynamic control of a robot arm based on neural networks [ J ]. Control Engineering Practice, 1997,5(4) : 485-492.

二级参考文献12

共引文献29

同被引文献6

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部