摘要
提出一种基于模糊LS-SVM传感器的非线性动态误差补偿器设计措施,在传感器与参考模型对输入激励响应的实测数据基础上,运用模糊LS-SVM回归算法构造补偿器,减小微硅加速度传感器因带宽有限引起的动态测量误差。既克服人工神经网络非线性动态补偿过程中易出现的局部极小问题,又减小在标准LS-SVM中一些非主要数据对模型精度的影响,在测试领域中有较好的应用前景。
A design method of the dynamic compensation for micro-silicon accelerometer sensors was presented based on the fuzzy least squares-support vector machine（fuzzy LS-SVM）. According to the measurement data of the step response of the sensor and the reference model, the compensator was constructed by fuzzy LS-SVM regression algorithm which reduced the dynamic errors because of the limited bandwidth of micro-silicon aceelerometer sensors. The method can overcome the local minima problem in dynamic compensation of neural networks and reduce the effect on model precision because of some extraessential data in standard LS-SVM, which has a potential future in the field of measurement.
出处
《中国测试》
CAS
北大核心
2012年第5期66-69,共4页
China Measurement & Test
关键词
模糊LS-SVM
微硅加速度传感器
动态补偿
仿真
fuzzy LS-SVM
micro-silicon aceelerometer sensors
dynamic compensation
simulation
