Robust output tracking of transverse flux machines using RBF neural network

被引：0

作者：

Karimi, HR ^{[1
]}

Babazadeh, A ^{[1
]}

Parspour, N ^{[1
]}

机构：

[1] Univ Teheran, Fac Engn, Dept Elect & Comp Engn, Tehran, Iran

来源：

2004 IEEE CONFERENCE ON ROBOTICS, AUTOMATION AND MECHATRONICS, VOLS 1 AND 2 | 2004年

关键词：

RBF network; output tracking; robust control; transverse flux machine;

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 presents an application of Radial Basis Function (RBF) in identification and control design of Transverse Flux Machines as nonlinear systems with unknown nonlinearity part. The 'technique of feedback linearization and H-infinity control are used to design an adaptive control law for compensating the unknown nonlinearity part, such the effect of cogging torque as a disturbance will be decreased onto the angle and angular velocity tracking performances.

引用

页码：496 / 501

页数：6

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