Fast filtering algorithm based on vibration systems and neural information exchange and its application to micro motion robot

Fast filtering algorithm based on vibration systems and neural information exchange and its application to micro motion robot
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基于振动系统和神经信息交换的快速滤波算法及其在微动机器人中的应用

DOI:
10.1088/1674-1056/23/1/010701
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发表时间:
2013
期刊:
影响因子:
1.7
通讯作者:
李满天
李满天
中科院分区:
物理与天体物理3区
文献类型:
--
作者:
高娃;查富生;宋宝玉;李满天

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提出了一种基于振动系统理论和神经信息交换方法的快速滤波算法。讨论了该方法的特点,包括推导过程和参数分析,并通过仿真和实用方法与各种滤波方法,如快速小波变换算法、粒子滤波法和我们开发的单自由度振动系统滤波算法进行了比较,验证了该方法的可行性和有效性。同时,比较表明,该快速滤波算法的显著优势在于其极快的滤波速度和良好的滤波性能。此外,将所开发的快速滤波算法应用于微动机器人导航定位系统中,对信号的预处理有很高的实时性要求。然后,利用预处理后的数据对微动机器人的航向角误差和姿态角误差进行估计。估计实验表明,该快速滤波算法具有较高的实用性。
This paper develops a fast filtering algorithm based on vibration systems theory and neural information exchange approach. The characters, including the derivation process and parameter analysis, are discussed and the feasibility and the effectiveness are testified by the filtering performance compared with various filtering methods, such as the fast wavelet transform algorithm, the particle filtering method and our previously developed single degree of freedom vibration system filtering algorithm, according to simulation and practical approaches. Meanwhile, the comparisons indicate that a significant advantage of the proposed fast filtering algorithm is its extremely fast filtering speed with good filtering performance. Further, the developed fast filtering algorithm is applied to the navigation and positioning system of the micro motion robot, which is a high real-time requirement for the signals preprocessing. Then, the preprocessing data is used to estimate the heading angle error and the attitude angle error of the micro motion robot. The estimation experiments illustrate the high practicality of the proposed fast filtering algorithm.
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发表时间: 2009-07
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