• CN:11-2187/TH
  • ISSN:0577-6686

›› 2014, Vol. 50 ›› Issue (6): 15-21.

• 论文 • 上一篇    下一篇

基于改进模糊推理的光纤陀螺温度漂移建模

赵曦晶;汪立新;何志昆;杨剑   

  1. 第二炮兵工程大学控制工程系
  • 出版日期:2014-03-20 发布日期:2014-03-20

Modeling of Temperature Drift Based on Improved Fuzzy Inference for Fiber Optic Gyroscope

ZHAO Xijing;WANG Lixin;HE Zhikun;YANG Jian   

  1. Department of Control Engineering, The Second Artillery Engineering University, Xi’an 710025
  • Online:2014-03-20 Published:2014-03-20

摘要: 光纤陀螺温度漂移建模是实现其温度补偿,提高测量精度的有效手段。通过实测数据分析,验证光纤陀螺的输出受温度和载体角速度的共同作用呈现复杂非线性。为准确描述这种复杂非线性关系以实现温度漂移高精度补偿,基于神经网络设计一种新型光纤陀螺温度漂移模糊系统结构,提出一种基于改进模糊推理的光纤陀螺温度漂移模型辨识新方法。由确定的模型结构设计模糊系统的模糊规则,并基于实测数据构建训练样本以被用于自适应调整变量隶属度函数的参数,从而建立基于误差方均根最小准则的光纤陀螺温度漂移补偿模型。试验结果表明,应用此方法得到的光纤陀螺温度漂移模型具有很高的精度、良好的适用性和预测性能。

关键词: 光纤陀螺;温度漂移;自适应神经网络模糊推理;综合补偿;非线性分析;模型辨识

Abstract: Modeling and compensation for the temperature drift is an effective method to improve the measurement precision of the fiber optic gyroscope(FOG). Due to the coupling effect of temperature and input rotation rate, the complicated nonlinearity of FOG output is aggravated. To describe the nonlinearity exactly and compensate the drift accurately, a new structure of the temperature drift compensation model is designed based on neural network and a novel identification approach based on improved fuzzy inference is proposed. According to the new determinate model structure, the fuzzy regulations of the fuzzy system are designed. The parameters of the member functions are adjusted adaptively using the training data, which is constructed by the actual measurement data. Then the compensation model is identified by fuzzy inference based on the least root square mean error criterion. The results show that the established model can obtain high accuracy, good applicability and attractive prophecy.

Key words: fiber optic gyroscope(FOG);temperature drift;adaptive neural network-fuzzy inference;comprehensive compensation;nonlinearity analysis;model identification

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