Real-Time Interval Type-2 Fuzzy Control of an Unmanned Aerial Vehicle with Flexible Cable-Connected Payload

Author:

Candan Fethi1ORCID,Dik Omer Faruk2,Kumbasar Tufan2,Mahfouf Mahdi1,Mihaylova Lyudmila1ORCID

Affiliation:

1. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK

2. Control and Automation Department, Istanbul Technical University, 34467 Istanbul, Turkey

Abstract

This study presents the design and real-time applications of an Interval Type-2 Fuzzy PID (IT2-FPID) control system on an unmanned aerial vehicle (UAV) with a flexible cable-connected payload in comparison to the PID and Type-1 Fuzzy PID (T1-FPID) counterparts. The IT2-FPID control has significant stability, disturbance rejection, and response time advantages. To prove and show these advantages, the DJI Tello, a commercial UAV, is used with a flexible cable-connected payload to test the robustness of PID, T1-FPID, and IT2-FPID controllers. First, the optimal coefficients of the compared controllers are found using the Big Bang–Big Crunch algorithm via the nonlinear UAV model without the payload. Second, once optimised, the controllers are tested using several scenarios, including disturbing the payload and the coverage path planning area to examine their robustness. Third, the controller performance results are evaluated according to reference achievement and point-based tracking under disturbances. Finally, the superiority of the IT2-FPID controller is shown via simulations and real-time experiments with a better overshoot, a faster settling time, and good properties of disturbance rejection compared with the PID and the T1-FPID controllers.

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automatic control of UAVs: new adaptive rules and type-3 fuzzy stabilizer;Complex & Intelligent Systems;2024-07-09

2. An Interacting Multiple Model Approach Based on Maximum Correntropy Student's T Filter;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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