论文标题
使用重力搜索算法调整非线性姿势滤波器的FLC
FLC tuned with Gravitational Search Algorithm for Nonlinear Pose Filter
论文作者
论文摘要
与其他姿势估计方法相比，非线性姿势（\ textIt {i.e，}态度和位置）过滤器的特征是更简单的结构和更好的跟踪性能。设计非线性姿势过滤器时的关键因素是误差函数的选择。非线性姿势过滤器设计的常规设计在快速适应和鲁棒性之间权衡。本文介绍了一种基于模糊规则的新实用方法，用于在线连续调整非线性姿势过滤器。使用图形搜索算法优化，考虑姿势误差及其变化率，使用图形搜索算法优化了每个输入和输出成员资格功能。所提出的方法具有高适应性特征和强大的鲁棒性水平。因此，提出的鲁棒和快速收敛性能的方法结果。仿真结果表明，考虑到不确定的测量和初始化的较大误差，提出的方法的有效性。
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.
