Design and Implementation Sliding Mode Controller Based on Radial Basis Function Neural Network for Synchronous Reluctance Motor

被引：0

作者：

Chen, Chien-An ^{[1
]}

Lin, Wen-Bin ^{[1
]}

Chiang, Huann-Keng ^{[2
]}

机构：

[1] Natl Yunlin Univ Sci & Technol, Grad Sch Engn Sci & Technolog, Touliu 640, Yunlin, Taiwan

[2] Natl Yunlin Univ Sci & Technol, Dept Elect Engn, Touliu 640, Yunlin, Taiwan

来源：

ICIEA: 2009 4TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-6 | 2009年

关键词：

Sliding Mode Control; Radial Basis Function Neural Network; synchronous reluctance motor; Lyapunov function; steep descent rule; INDUCTION-MOTOR; SPEED CONTROL; DRIVE; SYSTEMS;

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 a sliding mode control (SMC) design based on radial basis function neural network (RBFNN) to robust stabilization and disturbance rejection of the synchronous reluctance motor (SynRM) drive system. This method utilizes Lyapunov function and the steep descent rule to guarantee the convergence of the SynRM system asymptotically. Finally, we employ the experiments to validate the proposed method.

引用

页码：276 / +

页数：2

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