Adaptive Backstepping FNN Control for a Permanent Magnet Synchronous Motor Drive

被引：0

作者：

Lin, Chih-Hong ^{[1
]}

Lin, Chih-Peng ^{[2
]}

机构：

[1] Natl United Univ, Dept Elect Engn, Miaoli 360, Taiwan

[2] Su Mo Enterprise Co Ltd, Dept Engn, Taichung 403, Taiwan

来源：

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

关键词：

permanent magnet synchronous motor; fuzzy neural network; digital signal processor; FUZZY-NEURAL-NETWORK; SLIDING MODE CONTROL; NONLINEAR-SYSTEMS; DESIGN;

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：

The permanent magnet synchronous motor (PMSM) drive system using adaptive backstepping fuzzy neural network (ABFNN) control is investigated for the tracking of periodic reference inputs. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMSM servo drive. Then, an adaptive backstepping approach is proposed to compensate the uncertainties in the motion control system. With the proposed adaptive backstepping control system, the mover position of the PMSM drive possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic reference trajectories. Moreover, to further increase the robustness of the PMSM drive, a FNN uncertainty observer is proposed to estimate the required lumped uncertainty in the adaptive backstepping control system. The effectiveness of the proposed control scheme is verified by the experimental results.

引用

页码：2703 / +

页数：2

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