A new fuzzy logic-based adaptive complementary filter algorithm for UAV attitude estimation

Authors : Ömer Karal, Hasan Kazdal

Pages : 324-332

View : 43 | Download : 66

Publication Date : 2024-06-29

Article Type : Research Paper

Abstract :Micro Electro-Mechanical System (MEMS) Based Inertial Measurement Units (IMU) are widely used for attitude estimation in unmanned aerial vehicle (UAV) systems owing to their small, light weight and cost effectiveness. On the other hand, it has some disadvantages that influence performance, such as noisy output, low sensitivity, poor accuracy, and bias stability. Also, MEMS-based IMU sensors (accelerometers and magnetometers and gyroscopes) cannot provide adequate navigation solutions as a standalone system. Different sensor fusion techniques have been proposed in the literature to obtain reliable attitude estimation. However, most of these fail in situations such as nonlinear measurement models, nonlinear process dynamics, and long-range navigation. This article presents a new fuzzy rule-based complementary filter (CF) that combines magnetic field, angular velocity and acceleration measurements from low-cost MEMS-based IMU sensors to achieve a more robust attitude estimation in a UAV under dynamic motion. The proposed approach adjusts the cut-off frequency of the CF to the optimum value according to the variable dynamic motion of the system. Thus, the problem of constant cut-off frequency is eliminated and a more robust attitude estimation is achieved even with the varying movements of the system. Both real experiments and numerical simulations confirm the validity of the presented method.
Keywords : Tutum tahmini, Atalet ölçüm birimi, Bulanık mantık, Tamamlayıcı filtre, Gerçek zamanlı deneyler