凸轮许用压力角的合理确定

通过建立力学模型 ,对直动盘状凸轮机构进行了受力分析 ,指出凸轮压力角引用传统方法 ,即单一升程、回程许用压力角 [α1]=30°,[α2 ]=70°～ 80°,不合理。许用值应与机构的具体材料、摩擦状态、机构工作载荷以及从动件瞬间加速度大小有关。导出了凸轮机构许用压力角的理论数值。机构许用压力角与机构摩擦材料有关 ,摩擦系数越大 ,[α1]越小 [α2 ]越大 ;与机构摩擦性质有关 ,尖端凸轮机构较滚子凸轮机构 [α1]小 ,[α2 ]大 ;与机构工作载荷、从动件加速度大小有关 ,载荷越大、加速度越大时 ,则 [α1]越小 ,[α2

捷联寻的弹药惯性视线重构及制导系统设计

捷联导引头测量信息中耦合了弹体姿态信息,无法直接运用于制导指令解算。基于下视的捷联寻的方案,建立了从探测视线信息和弹体姿态信息中提取惯性视线角的理论解耦模型以及在倾斜稳定情况下的简化形式。通过非线性微分滤波器——跟踪微分器获得平滑的惯性视线角速率,设计了捷联寻的弹药制导综合系统。弹道仿真结果表明:基于下视的捷联寻的方案能够有效实现近程制导弹药的精确制导,具有一定的工程价值。

一种基于INS数据融合提高FADS攻角侧滑角动态性能的方法

探索了一种提高FADS攻角、侧滑角动态性能的方法。首先介绍了算法的结构和惯性攻角、侧滑角解算方法，然后针对某飞行数据分析其互补滤波器时间常数设置。并对该数据进行仿真计算了攻角、侧滑角两个通道的数据。仿真结果表明、融合后的数据可以有效地提高FADS的动态性能。

履带式移动机器人越障稳定性分析

通过对自主研制的履带式排爆机器人跨越障碍过程的稳定性进行分析,分析机器人爬楼梯的侧向稳定性,建立机器人越障运动学、动力学方程,导出机器人越障时产生的惯性角,并以此作为机器人越障动态稳定性指标来判断机器人的稳定性,最终得出机器人在跨越障碍时,以前接地点落地碰撞引起的冲击最为严重。

全捷联小型弹药制导系统设计

围绕适用于小型无人机、单兵等平台的微小型弹药制导化需求,提出了基于捷联导引头和捷联惯导的全捷联制导控制方案。针对全捷联体制无法直接提供有效制导信息的问题,导出了惯性视线速率的理论方程及滚转稳定条件下的实用形式,设计了非线性微分器以实现稳定的视线信息数值微分。给出了作为内回路的PI校正两回路过载驾驶仪。分别进行了机载平台和单兵发射的仿真。结果表明:全捷联技术可以有效解决小射程条件下制导弹药的小型化、精确化,多约束条件下的制导控制系统设计是应用的关键。

Structure design and simulation of MEMS vibrating ring gyroscope

MEMS gyroscope is a new inertial navigation sensor,which can measure the input angular rate of sensitive axis using Coriolis effect.Compared to the conventional gyroscope,it owns many unique advantages.A novel structure of vibrating ring gyroscope is proposed and the finite element model of the oscillator is established based on MEMS technology.Through the modal analysis,the natural frequency and mode shapes of the oscillator are obtained.By analyzing the effects of the structural parameters on the mode shapes and frequency of the harmonic oscillator,the optimal design parameters are got.The frequency difference between the operating mode and the other modes is greater than 1kHz after optimization,which can avoid the frequency coupling of the operating mode and other vibrating modes of the oscillator.The simulation results show that the performance parameters of the ring structure meet the design requirements and have obvious advantages.

超声波阵列的飞行高度与姿态测量方法

针对无人机近地面降落阶段对相对高度及姿态精确测量的需求,以固定翼无人机为对象,设计了多路超声波测距传感器在无人机上的新型布局方式。利用空间几何关系,建立相对高度及姿态计算模型,测得四个固定点的高度,为无人机着陆提供精确的相对高度及姿态角信息。充分利用布置在无人机不同位置的测距传感器之间的几何关系,直接获得姿态角,提高了无人机降落阶段的安全性。实验结果表明,能够及时有效地提供给控制台无人机着陆时的相对高度及姿态信息,准确指引无人机的安全降落。

基于无迹卡尔曼的全捷联旋转弹导引信息估计

以旋转弹的全捷联导引头为研究对象,重点研究了旋转弹的全捷联导引头视线角及视线角速率估计方法。全捷联导引头的结构和传统速率陀螺导引头有较大差别,其测量系统与弹体固联,导引头只能获得弹体坐标系下的测量信息,并且测量信息中耦合有弹体姿态信息,无法直接用于旋转弹的控制制导。根据坐标系之间的转换关系建立了旋转弹惯性视线角的数学模型和视线角解耦模型,从而进一步确立旋转弹惯性视线角估计的数学模型。选用无迹卡尔曼滤波方法(UKF),设计出卡尔曼滤波器,对估计到的含有噪声信息的视线角进行滤波;最后进行数学仿真,验证了视线角估计数学模型的有效性,与扩展卡尔曼滤波方法(EKF)和容积卡尔曼滤波方法(CKF)相比,UKF对于全捷联旋转弹的导引信息估计有更高的精度。

基于卡尔曼滤波的成像旋转弹跟踪系统设计

针对采用捷联稳定方案的旋转弹,为实现用数字计算方法提取比例导引所需的弹目惯性视线角速率信号,对一种基于卡尔曼滤波的成像旋转弹跟踪系统设计进行了研究。将目标的随机加速机动视作修正的瑞利-马尔科夫过程,与视线运动方程联立,建立了机动目标跟踪系统数学模型。由稳定平台的惯性测量元件实现对弹体姿态角的计算,另通过大视场捕获目标,获取目标相对光轴的误差角,综合两者可得目标相对惯性空间的视线角,对视线角进行数字微分获得视线角速度。其中,为避免放大测量噪声,采用自适应卡尔曼滤波法估计视线角速度。闭环仿真结果表明:与低通滤波算法相比,自适应卡尔曼滤波算法的精度高,对测量噪声抑制好,可获得比例导引所需的惯性视线角速率和跟踪角误差的滤波值,从而实现高精度控制。

Research on coning compensation algorithms for SINS of angular rate input

To compensate the coning error of Strap-down Inertial Navigation Systems (SINS) under high dynamic angular motion, many rotation vector algorithms have been developed using angle increments information. However, most SINS use angular rate gyros. Aimed at this problem, 18 algorithms are derived based on analysis of the conventional algorithms, and corresponding coning error expressions are given. At last simulation is made which indicates that the new algorithms have much higher precision.

Sensor fusion for heading angle estimation based on random forest algorithm

To improve the accuracy of the calculation of a heading angle under magnetic interference,magnetometers and inertial measurement units(IMUs)were fused.The observation value of the heading angle was deduced on the basis of the modeling of the magnetometer error and the analysis of the relation of the magnetometer triaxial output and the distribution characteristics of the magnetic field at two adjacent time periods.Meanwhile,the gyro state and angular velocity increment were used as the basis of the IMU to calculate the prediction value of the heading angle.With the changes in the heading angle and environmental interference,a random forest(RF)algorithm was used to iteratively calculate the weights to fuse the observation value of the heading angle based on the magnetometer and the prediction value of the heading angle based on the IMU.The results show that relative to the common sensor fusion method,the proposed sensor fusion method based on the RF algorithm achieved an approximate 60%improvement in heading angle accuracy.Hence,the proposed method can effectively improve the accuracy of the heading angle under magnetic interference by using an RF algorithm to calculate the output weights of the magnetometer and IMU.

Initial alignment for low-cost attitude and heading reference systems

MEMS （micro electro mechanical systems） inertial navigation system ~, Mll＇~3） nas Been WllUly used in robots for its low-cost. The MINS and magnetometers are commonly the component parts of the attitude and heading reference systems （AHRS）, which provide pitch and roll angles relative to the earth gravity vector, and heading angle relative to the north. However, the performance of sen- sors with low cost AHRS is not so good. The gyros are not sensitive enough to observe the earth an- gular velocity, so the traditional technique like alignment algorithm is invalid. The measurements of gyros become useless to determine the initial attitude matrix from navigation frame to body frame. The alignment algorithm is computed by the accelerometers and magnetometers. The process is es- tablished as an optimization problem of finding the maximum eigenvector. Meanwhile the sensitive analysis with respect to the biases of accelerometers is proposed. Then the recursive least squares al- gorithm （RLSA） is introduced. The comparison between the proposed method and RLSA is provid- ed. The results demonstrate its accuracy favorably and verify the feasibility of the proposed algo- rithm.