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应用科学学报

• 信号与信息处理 • 上一篇    

运用神经网络代数算法的陀螺仪非线性误差补偿

马斌良， 黄玉美， 刘蜀阳， 陈亮   

  1. 西安理工大学 机械与精密仪器工程学院，陕西 西安710048
  • 收稿日期:2007-10-29 修回日期:2008-01-09 出版日期:2008-07-31 发布日期:2008-07-31

Nonlinear Error Compensation of Gyroscope Using Algebra Algorithm of Neural Networks

MA Bin-liang, HUANG Yu-mei, LIU Shu-yang, CHEN Liang
  

  1. School of Mechanical and Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
  • Received:2007-10-29 Revised:2008-01-09 Online:2008-07-31 Published:2008-07-31

被引次数

6

摘要： 为了提高陀螺仪的测量精度，基于神经网络代数算法提出一种新的非线性误差补偿模型。由于该算法将复杂非线性优化问题转化为线性代数方程组问题，所以该模型具有速度快、实时性好，能实现样本空间精确映射的优点。通过实验对比证明该模型比曲线拟合精度要高。多次重复性实验证明该模型能够将误差限制在0.1o/s以内，满足实际控制要求。

关键词: 陀螺仪, 神经网络, 代数算法, 非线性误差补偿

Abstract: To improve measurement precision of gyroscope, a novel nonlinear error compensation model is proposed using an algebra algorithm of neural networks. The model has advantages of real-time processing and precision mapping in the sample space because the algorithm transforms the complicated nonlinear optimization problem into linear algebraic equations. Compared to polynomial fitting, the proposed model has better precision. Experiments show that the model can reduce error to 0.1o/s and meet practical control needs.

Key words: gyroscope, neural networks, algebra algorithm, nonlinear error compensation