非线性位姿滤波器的引力搜索算法调谐的FLC
FLC tuned with Gravitational Search Algorithm for Nonlinear Pose Filter
摘要：
与其它姿态估计方法相比，非线性姿态（\textit{i.e,}姿态和位置）滤波器具有结构简单、跟踪性能好的特点。设计非线性姿态滤波器时的一个关键因素是误差函数的选择。传统的非线性姿态滤波器设计在快速适应和鲁棒性之间进行权衡。本文介绍了一种新的实用方法，基于模糊规则的在线连续调整的非线性位姿滤波器。每个输入和输出的隶属度函数进行优化调整，使用图形搜索算法优化，同时考虑位姿误差和它的变化率。该方法具有自适应性强、鲁棒性强等特点。因此，该方法具有鲁棒性和快速收敛性.仿真结果表明，在观测不确定和初始化误差较大的情况下，该方法是有效的。
英文摘要：
Nonlinear pose (\textit{i.e,} attitude and position) filters are characterized with simpler structure and better tracking performance in comparison with other methods of pose estimation. A critical factor when designing a nonlinear pose filter is the selection of the error function. Conventional design of nonlinear pose filter design trade-off between fast adaptation and robustness. This paper introduces a new practical approach based on fuzzy rules for on-line continuous tuning of the nonlinear pose filter. Each of input and output membership functions are optimally tuned using graphical search algorithm optimization considering both pose error and its rate of change. The proposed approach is characterized with high adaptation features and strong level of robustness. Therefore, the proposed approach results of robust and fast convergence properties. The simulation results show the effectiveness of the proposed approach considering uncertain measurements and large error in initialization.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
