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

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ID: 94357
2019
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Abstract
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 (δi), along with disturbance attenuation parameter γ. 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. Keywords: Interacting multiple models, Integrated navigation system, Multi-mode estimation, Nonlinear fuzzy adaptive filter, Sensor data fusion, UAV localization
Reference Key
mostafa2019achinese Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors MOSTAFA, Elzoghby;FU, Li;IBRAHIM.I., Arafa;USMAN, Arif;
Journal chinese journal of aeronautics
Year 2019
DOI
DOI not found
URL
http://www.sciencedirect.com/science/article/pii/S1000936119300937
Keywords
Medicine Technology (General) Engineering (General). Civil engineering (General) Technology Science (General) Science motor vehicles. aeronautics. astronautics meteorology. climatology electronic computers. computer science

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