Novel, similarity-based non-singleton fuzzy logic control for improved uncertainty handling in quadrotor UAVs

Fu, Changhong and Sarabakha, Andriy and Kayacan, Erdal and Wagner, Christian and John, Robert and Garibaldi, Jonathan M. (2017) Novel, similarity-based non-singleton fuzzy logic control for improved uncertainty handling in quadrotor UAVs. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), 9-12 July 2017, Naples, Italy. (In Press)

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Abstract

As non-singleton fuzzy logic controllers (NSFLCs) are capable of capturing input uncertainties, they have been effectively used to control and navigate unmanned aerial vehicles (UAVs) recently. To further enhance the capability to handle the input uncertainty for the UAV applications, a novel NSFLC with the recently introduced similarity-based inference engine, i.e., Sim-NSFLC, is developed. In this paper, a comparative study in a 3D trajectory tracking application has been carried out using the aforementioned Sim-NSFLC and the NSFLCs with the standard as well as centroid composition-based inference engines, i.e., Sta-NSFLC and Cen-NSFLC. All the NSFLCs are developed within the robot operating system (ROS) using the C++ programming language. Extensive ROS Gazebo simulation-based experiments show that the Sim-NSFLCs can achieve better control performance for the UAVs in comparison with the Sta-NSFLCs and Cen-NSFLCs under different input noise levels.

Item Type: Conference or Workshop Item (Paper)
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Eprints, Support
Date Deposited: 26 Apr 2017 07:46
Last Modified: 13 Oct 2017 18:41
URI: http://eprints.nottingham.ac.uk/id/eprint/42286

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