摘要
研究小型无人机姿态稳定性能控制的问题。针对小型无人机在应用扩展卡尔曼滤波(EKF)融合MEMS的测量值时,融合的结果稳定性较差、易发散的问题,提出了一种模糊自适应EKF算法(FAEKF),利用四元数描述的方法,融合MEMS的测量信息对无人机姿态角进行测量,并设计了模糊自适应控制器实时修正观测噪声矩阵。仿真结果表明,提出的算法能准确的测量出姿态角,且通过与EKF算法仿真结果对比可以看出,FAEKF在稳定性能控制上有较明显改善,有效抑制了姿态角的发散,说明提出算法的有效性,为小型无人机姿态稳定性能的控制提供了一种科学的手段。
In order to overcome poor stability and easy divergence in the extended Kalman filter (EKF) algorithm fused the measurement value of the MEMS device, a fuzzy adaptive EKF (FAEKF) algorithm is proposed based on quaternion, the MEMS information is fused to measure the attitude angle, and the fuzzy logic adaptive controller is designed to modify the observation noise matrix. The simulation results show that the proposed method can accurately measure the attitude angle, and the comparison results with the conventional EKF prove that the FAEKF algorithm has obvious improvement in stability, and the divergence of attitude angle is effectively suppressed.
作者
柏植
凌六一
韩涛
徐雨
BAI Zhi;LING Liu-yi;HAN Tao;XU Yu(College of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan Anhui 232001, China)
出处
《计算机仿真》
北大核心
2017年第11期16-20,共5页
Computer Simulation