Sliding Mode Control of Magnetic Levitation System Using Radial Basis Function Neural Networks

被引：0
|
作者：
Aliasghary, M. [1 ]
Jalilvand, A. [2 ]
Teshnehlab, M. [3 ]
Shoorehdeli, M. Aliyari [3 ]
机构：
[1] Islamic Azad Univ, Sci & Res Branch, Dept Elect Engn, Tehran, Iran
[2] Zanuni Univ, Elect Engn Dept, Zanjan, Iran
[3] KN Toosi Univ, Elect Engn Dept, Tehran, Iran
来源：
2008 IEEE CONFERENCE ON ROBOTICS, AUTOMATION, AND MECHATRONICS, VOLS 1 AND 2 | 2008年
关键词：
Radial basis function; Sliding mode; Magnetic levitation system; Sliding surface;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper has developed a sliding mode controller (SMC) based on a radial basis function model for control of Magnetic levitation system. Adaptive neural networks controllers need plant's Jacobain, but here this problem solved by sliding surface and generalized learning rule in case to eliminate Jacobain problem. The simulation results show that this method is feasible and more effective for Magnetic levitation system control.
引用
收藏
页码：545 / +
页数：2
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