基于微机电系统洛伦兹平台角速度估计

Angular Velocity Estimation Using Micro-electro-mechanical System Sensors with Applications in Lorentz Platform

针对洛伦兹惯性稳定平台对高带宽和高精度角速率需求,提出了基于微机电系统(micro-electro-mechanical system,MEMS)组合传感器的最优速度估计算法。MEMS组合传感器由陀螺仪和加速度计组成,MEMS陀螺仪由于自身特性在速度估计中提供低频速度信息,而加速度计则提供高频信息。最优估计器通过将低频信号与高频信息融合,采用最优控制与估计算法进行速度解算与估计。实验表明,频率在20 Hz内,运动角度在±60°内,MEMS组合传感器速度拟合周期不超过5%,稳定拟合误差不超过7.5%,可以满足平台稳定偏转控制需求。最优状态估计器能在时域与频域上提供无差、高性能的角速度信号。

The performance of Lorentz inertial stabilization platform is strongly related to the bandwidth and accuracy of the angular velocity signals.The development of an optimal state estimator for sensing inertial velocity using micro-electro-mechanical system(MEMS)combined sensors was discussed.MEMS combined sensors composed by gyroscopes and accelerometers.The MEMS gyroscope mainly contributes to the low-frequency components with its own characteristics,and the accelerometer mainly contributes to the high-frequency components.The optimal estimator uses optimal control and estimation algorithms to calculate and estimate speed by fusing low-frequency signals and high-frequency information.Experimental results show that with the frequency in 20 Hz and angle of deflection in±60°,the MEMS combined sensor can reach lower than 5%speed fitting period errors,and the stable fitting errors lower than 7.5%,which can meet the stable deflection control requirements of the platform.The optimal state estimator can provide zero-difference and high performance angular velocity signals in time domain and frequency domain.