Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control

Ayad Al-Mahturi; Fendy Santoso; Matthew A. Garratt; Sreenatha G. Anavatti

doi:10.1109/ACCESS.2021.3107906

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Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control

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Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control

Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt and Sreenatha G. Anavatti

IEEE access, Vol.9, pp.119520-119532

25/08/2021

DOI: https://doi.org/10.1109/ACCESS.2021.3107906

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Abstract

Interval type-2 fuzzy control

disturbance rejection

UAV

Lyapunov stability

real-time flight tests

This paper aims to design an enhanced self-adaptive interval type-2 fuzzy control system (ESAF2C) for stabilization of a quadcopter drone under external disturbances. Due to the ability to accommodate the footprint-of-uncertainty (FoU), an interval type-2 Takagi-Sugeno fuzzy scheme is employed to directly address the uncertainties in the nonlinear system. Sliding mode control (SMC) is utilized to optimize the upper and lower parameters of our proposed ESAF2C system using a self-tuning technique. The `Enhanced Iterative Algorithm with Stop Condition' type-reducer is accommodated in the proposed design for its suitability to real-time implementation. To handle external disturbances and the ground effect in the closed-loop flight control system, a robustness term is added to the control effort. Lyapunov theory is applied to prove the stability of our closed loop control system. Moreover, we study the measurement noise effect for different levels of noise powers using our proposed technique. The efficacy of the proposed controller is investigated in a hovering quadcopter drone through numerical simulations and real-time flight tests in the presence of external disturbances. We highlight the disturbance rejection capability of our proposed control system with respect to type-1 fuzzy and conventional PID controllers.

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Title: Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control
Creators: Ayad Al-Mahturi - University of New South Wales
Fendy Santoso - University of New South Wales
Matthew A. Garratt - University of New South Wales
Sreenatha G. Anavatti - University of New South Wales
Publication Details: IEEE access, Vol.9, pp.119520-119532
Publisher: IEEE
Grant note: Australian Government Research Training Program Scholarship (10.13039/100015539)
Identifiers: 991013092526402368
Copyright: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
Academic Unit: Faculty of Science and Engineering
Language: English
Resource Type: Journal article

Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control

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