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Sensors 2014, 14(9), 17600-17620; doi:10.3390/s140917600

Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter

1
School of Automation Science and Electrical Engineering, Beihang University, 37 Xueyuan Road, Haidian District, 100191 Beijing, China
2
School of Control and Automation, Ecole Militaire Polytechnique, EMP, Bordj El Bahri, 16111 Algiers, Algeria
*
Author to whom correspondence should be addressed.
Received: 6 May 2014 / Revised: 5 September 2014 / Accepted: 12 September 2014 / Published: 19 September 2014
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)

Abstract

Although nonlinear H∞ (NH∞) 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∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ 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∞ filter. View Full-Text
Keywords: UAV localization; sensor data fusion; Extended Kalman Filter (EKF); Nonlinear H∞ (NH∞); Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter UAV localization; sensor data fusion; Extended Kalman Filter (EKF); Nonlinear H∞ (NH∞); Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Outamazirt, F.; Li, F.; Yan, L.; Nemra, A. Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter. Sensors 2014, 14, 17600-17620.

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