A solution of UAV localization problem using an interacting multiple nonlinear fuzzy adaptive H_(∞)models filter algorithm

作     者：Elzoghby MOSTAFA Li FU Arafa IBRAHIM.I. Arif USMAN 

作者机构：School of Automation Science and Electrical EngineeringBeihang University School of Control and AutomationMTCAl-Khalifa Al-Maamoon Street Kobry Elkobbah 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2019年第32卷第4期

页      面：978-990页

核心收录：

学科分类：08[工学] 081105[工学-导航、制导与控制] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：supported by a grant from the National Natural Science Foundation of China(No.61375082) 

主　　题：Interacting multiple models Integrated navigation system Multi-mode estimation Nonlinear fuzzy adaptive filter Sensor data fusion UAV localization 

摘      要：The purpose of this research is to improve the robustness of the autonomous system in order to improve the position and velocity estimation of an Unmanned Aerial Vehicle(UAV).Therefore, new integrated SINS/GPS navigation scheme based on Interacting Multiple Nonlinear Fuzzy Adaptive H_∞ Models(IMM-NFAH_∞) filtering technique for UAV is presented. The proposed IMM-NFAH_∞ strategy switches between two different Nonlinear Fuzzy Adaptive H_∞(NFAH_∞) filters and each NFAH_∞ filter is based on different fuzzy logic inference systems. The newly proposed technique takes into consideration the high order Taylor series terms and adapts the nonlinear H_∞ filter based on different fuzzy inference systems via adaptive filter bounds(di),along with disturbance attenuation parameter c. Simulation analysis validates the performance of the proposed algorithm, and the comparison with nonlinear H_∞(NH_∞) filter and that with different NFAH_∞ filters demonstrate the effectiveness of UAV localization utilizing IMM-NFAH_∞ filter.