Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H infinity Filter

作者：Outamazirt Fariz^*; Li Fu; Yan Lin; Nemra Abdelkrim

来源：Sensors (Switzerland), 2014, 14(9): 17600-17620.

DOI：10.3390/s140917600

• UAV localization
• sensor data fusion
• Extended Kalman Filter (EKF)
• Nonlinear H infinity (NH infinity)
• Fuzzy Adaptive Nonlinear H infinity (FANH infinity) filter

Although nonlinear H infinity (NH infinity) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH infinity filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H infinity (FANH infinity) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH infinity filter continually adjusts the higher order of the Taylor development thorough adaptive bounds (delta(i)) and adaptive disturbance attenuation (gamma), which significantly increases the UAV localization performance. The results obtained using the FANH infinity navigation filter are compared to the NH infinity navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH infinity filter.

• 出版日期2014-9
• 单位北京航空航天大学