Adaptive fading Kalman filter with an application

A new adaptive state estimation algorithm, namely adaptive fading Kalman filter (AFKF), is proposed to solve the divergence problem of Kalman filter. A criterion function is constructed to measure the optimality of Kalman filter. The forgetting factor in AFKF is adaptively adjusted by minimizing the defined criterion function using measured outputs. The algorithm remains convergent and tends to be optimal in the presence of model errors. It has been successfully applied to the headbox of a paper-making machine for state estimation.

基于多传感器融合的组合导航方法研究

本文提出一种基于多传感器融合的组合导航方法,能够在小型旋翼无人机上实现低成本、高精度导航定位.该方法通过建立导航系统的机械编排模型,设计了一个17状态的扩展卡尔曼滤波器(EKF).对加速计的零偏和陀螺仪的漂移进行在线估计,实时的补偿传感器的测量误差.从而对旋翼无人机的速度、位置、角速度和姿态等参数进行精确的估计.通过对实际飞行数据仿真实验,并对比参考的导航系统,证明该方法在飞机的全包线飞行下均能够解算出可靠的导航信息。

基于模型参数估计的履带式移动机器人航向保持

履带式移动机器人运动时,由于受到系统误差及履带地面接触效应等不确定因素的影响,会导致航向及路径偏差。本文采用模型参数估计的方法达到履带式移动机器人路径保持的目的。首先,考虑履带与地面的滑动效应,建立起机器人运动学模型;然后,对于模型中受环境影响的参数,利用扩展卡尔曼滤波进行在线估计;最后,采用合适的观测值实现闭环控制。通过在履带式极地冰雪面移动机器人的实验研究,验证所提方法的可行性和有效性。

移动机器人几何-拓扑混合地图的构建及自定位研究

基于墙角、房门和通路等高级环境特征的辨识与提取,依据几何和拓扑环境模型完成混合地图的构建,并根据混合地图的特点,提出在局部几何环境采用扩展卡尔曼滤波算法实现移动机器人的位姿跟踪,而在拓扑地图的节点位置则根据绑定的高级环境特征进行位姿再校正的混合定位方法.将该方法应用于实际移动机器人平台,所得结果证明了方法的有效性和实用性.

估计从UUV航行参数的混合坐标系下的EKF算法

在主从式UUV 协作系统中，由于定位和导航的需要，要求尽快估计出从UUV 的航行参数，但通常所用的递推最小二乘（RLS）算法，其初始方位测量对滤波结果影响大且存在收敛速度慢、计算精度低的缺点，难以满足应用需求，而推广卡尔曼滤波（EKF）算法能较好地克服上述问题。在直角坐标系下（CEKF），方位信息与距离信息相互耦合导致初始振荡剧烈，改为混合坐标系（MEKF）后问题得到了极大的改善。最后，通过仿真及现场试验验证了此改进方法的有效性。

基于多普勒和光纤陀螺水下机器人导航系统研究

对基于DVL和FOG的导航方法进行研究,设计了导航方法的无缆水下机器人导航系统,分析导航系统的主要误差源,采用扩展Kalman滤波算法辨识传感器的安装偏差,通过湖试数据验证了该算法的稳定性和正确性。

COMPARATIVE-STUDY OF KALMAN FILTERING, SYNCHRONOUS EXCITATION AND NUMERICAL DERIVATIVE TECHNIQUES IN FLUOROMETRY

The performance of Kalman filtering, synchronous excitation and numerical derivative techniques for the resolution of overlapping emission spectra in spectrofluorimetry was studied. The extent of spectrum overlap was quantitatively described by the separation degree D(s), defined as the ratio of the peak separation to the full width at half-maximum of the emission spectrum of the interferent. For the system of Rhodamine B and Rhodamine 6G with a large D(s) of about 0.4, both Kalman filtering and synchronous techniques are able to resolve the overlapping spectra well and to give satisfactory results while the derivative spectra are still overlapped with each other. Moreover, the sensitivities are greatly decreased in derivative techniques. For more closely spaced spectra emitted by the complexes of Al and Zn with 7-iodo-8-hydroxyquinoline-5-sulphonic acid (Ferron)-hexadecyltrimethylammonium bromide, the synchronous excitation technique cannot completely separate the overlapping peaks, although it increases the separation degree from 0.25 in the conventional spectra to 0.37 in the synchronous spectra. On the other hand, Kalman filtering is capable of resolving this system. When the Al/Zn intensity ratio at the central wavelength of Al was > 1, however, the accuracy and precision of the estimates for Zn concentration produced by the Kalman filter became worse. In this event, the combination of synchronous excitation and Kalman filtering can much improve the analytical results.

RESOLUTION OF CLOSELY SPACED LINES WITH KALMAN FILTERING IN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION-SPECTROMETRY

Effects of some factors on the performance of our Kalman filter in discrimination of closely spaced overlapping signals were investigated. The resolution power of the filter for overlapping lines can be strengthened by reduction of the step size in scans. The minimum peak separation of two lines which the Kalman filter can effectively handle generally equals two to three times the step size in scans. Significant difference between the profiles of the analysis and interfering lines and multiple lines from matrix in the spectral window of the analysis line are very helpful for the Kalman filter to discern closely spaced analysis and interfering signals correctly, which allow the filter well to resolve the line pair with very small peak distance or even the entirely coincident lines.

KALMAN FILTERING FOR RESOLUTION OF OVERLAPPING LINES IN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION-SPECTROMETRY

A Kalman filter was developed for resolving overlapping lines in inductively coupled plasma atomic emission spectrometry (ICP-AES) and evaluated experimentally with the determination of La in the presence of Ho, and Cu in the presence of Pr. The whiteness of the innovation sequence for an optimal filter was explored to be the criterion for the correction of the wavelength positioning errors which may occur in spectral scans. Under the conditions of the medium-resolution spectrometer and 1.5 pm step size in scans, the filter effectively resolved the Cu/Pr line pair having a small peak separation of 4.8 pm. For the La/Ho line pair with a peak distance of 9.8 pm, an unbiased estimate for La concentration was still obtained even when the signal-to-background ratio was down to 0.048. Favourable detection limits for real samples were achieved. Unstructured backgrounds were modeled theoretically and all spectral scans therefore did not require the correction for solvent.

Information system for ICP-AES in Windows environment

An information system for inductively coupled plasma atomic emission spectrometry (TCP-BES) in MS Windows environment was developed based on the previous work in the laboratory. The system contains the data of about 28 000 spectral lines and a function of ICP spectral simulation,so it would be very helpful for line selection. The system also contains the Kalman filter and factor analysis programmes written with MS Visual Basic(version 4.0), which can be used for spectral interference correction and peak position optimization. A large amount of real spectral scanning data of rare earth elements were included in the system for user's references. All these characteristics made the system more useful and practical.

东中国海区域海浪同化系统设计与研究

针对目前海浪同化中没有适合东中国海区的业务应用系统，以及缺乏集合卡尔曼滤波方法（Ensemble Kalman Filter，EnKF）的应用的现状，设计了东中国海区域海浪同化系统。首先比较了目前常用的各种资料同化方法，指出各种同化方法的实质都是一种滤波过程，并选取最优插值方法（Optimal Interpolation，OI）和EnKF方法开展同化试验，动力模式选取WAVEWATCH III，观测资料为Topex/Poseidon卫星高度计观测波高。然后用观测法研究了模式预报误差协方差的统计性质，指出误差相关距离尺度在3°至6°之间。最后用22001号浮标观测资料验证了两个同化系统2000年8月的有效波高计算值，结果表明OI方案的同化系统对有效波高的均方根误差减少了9.0%，系统运行稳定，可应用于业务化部门；EnKF方案的同化系统在集合样本数为50的情况下，对有效波高的均方根误差减少了6.0%，用EnKF方法同化有效波高是可行的。

一种基于状态方差阵对角相似分解的UKF 算法

在强非线性和复杂性的系统下，普通对称采样UKF 算法存在稳定性问题。为此，本文提出了基于状态方差阵对角相似分解的UKF 算法来保证算法的状态方差阵半正定。同普通对称采样UKF 算法比较，该算法降低了对状态方差阵的正定性要求。仿真试验验证了该方法的有效性。

基于MIT规则的自适应Unscented卡尔曼滤波及其在旋翼飞行机器人容错控制的应用

提出一种新颖的基于MIT规则的自适应Unscented卡尔曼滤波(Unscented Kalman filter,UKF)算法,用来进行参数以及状态的联合估计。针对旋翼飞行机器人执行器提出一种执行器健康因子(Actuator health coefficients,AHCs)的故障模型结构,应用自适应UKF对AHCs参数进行在线估计,将联合估计的状态以及故障参数引入基于模型的反馈线性化控制结构,组成完整的容错控制系统。提出的自适应UKF算法以及容错控制结构经过中科院沈阳自动化研究所ServoHeli-20旋翼无人智能平台数学模型进行仿真试验验证,效果良好。

全地形移动机器人轮-地几何接触角估计

研究全地形移动机器人在不平坦地形中轮-地几何接触角的实时估计问题.本文以带有被动柔顺机构的六轮全地形移动机器人为对象,抛弃轮-地接触点位于车轮支撑臂延长线上这一假设,通过定义轮-地几何接触角δ来反映轮-地接触点在轮缘上位置的变化和地形不平坦给机器人运动带来的影响,将机器人看成是一个串-并联多刚体系统,基于速度闭链理论建立考虑地形不平坦和车轮滑移的机器人运动学模型,并针对轮-地几何接触角δ难以直接测量的问题,提出一种基于模型的卡尔曼滤波实时估计方法.利用卡尔曼滤波对机器人内部传感器的测量值进行噪声处理,基于机器人整体运动学模型对各个轮-地几何接触角进行实时估计,物理实验数据的处理结果验证了本文方法的有效性,从而为机器人运动学的精确计算和高质量的导航控制奠定了基础.

基于主动建模的无人直升机增强LQR控制

为了解决无人直升机控制问题,通过把主动建模与LQR(Linear Quadratic Regulator)控制相结合,提出一种能补偿模型差的控制方法。该方法在悬停状态下,采用简化模型设计LQR控制器,并通过UKF(Un-scented-Kalman-Filter)在线估计简化模型与全状态模型的模型差,使用模型差作为补偿项对LQR控制增强。针对实际直升机动力学模型进行仿真,验证了基于UKF的估计和增强LQR控制的有效性。仿真实验结果证明,基于UKF的主动建模技术能够快速估计状态和参数变化,并且增强LQR控制能够使系统适应模型不确定性。