光纤陀螺漂移误差的T-S模糊建模补偿算法

基于G-K聚类算法辨识T-S模糊模型前件参数理论,并采用最小二乘法辨识T-S模糊模型后件参数的误差模型,研究了一种光纤陀螺温度漂移误差的非线性补偿算法。在建立该模型的基础上对光纤陀螺零位输出进行了补偿,计算结果表明采用该种方法能够在不完全了解陀螺误差机理的情况下对其进行有效的补偿。其绝对误差与未补偿相比较降低了99%,同线性拟合补偿相比降低了96%和神经网络补偿比较降低了10%,其误差方差分别减少99%,98%,20%。

Drift error compensation algorithm for fiber optic gyro based on T-S fuzzy modeling

A drift error nonlinear compensation algorithm for Fiber Optic Gyro (FOG) is presented based on T-S fuzzy model with the antecedent parameters identified by G-K clustering algorithm and the error model of T-S fuzzy model with the consequent parameters identified by least square algorithm. The computed results show that this model can compensate the original data effectively, while the error principles of FOG do not need to be understood well. Comparing with the original data, compensation with linear fitting and compensation with neural network, the absolute error of the proposed model reduces by 99%, 96% and 10%, respectively. The error variance reduces by 99%, 98% and 20%, respectively. The results indicate that this proposed algorithm can be simply operated with high precision and easy to realize in engineering.