UAV Power Line Tracking Control Based on a Type-2 Fuzzy-PID Approach

Author:

Pussente Guilherme A. N.1ORCID,de Aguiar Eduardo P.2ORCID,Marcato Andre L. M.1ORCID,Pinto Milena F.3ORCID

Affiliation:

1. Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil

2. Department of Industrial and Mechanical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil

3. Federal Center of Technological Education of Rio de Janeiro (CEFET/RJ), Rio de Janeiro 20271-110, Brazil

Abstract

A challenge for inspecting transmission power lines with Unmanned Aerial Vehicles (UAVs) is to precisely determine their position and orientation, considering that the geo-location of these elements via GPS often needs to be more consistent. Therefore, a viable alternative is to use visual information from cameras attached to the central part of the UAV, enabling a control technique that allows the lines to be positioned at the center of the image. Therefore, this work proposes a PID (proportional–integral–derivative) controller tuned through interval type-2 fuzzy logic (IT2_PID) for the transmission line follower problem. The PID gains are selected online as the position and orientation errors and their respective derivatives change. The methodology was built in Python with the Robot Operating System (ROS) interface. The key point of the proposed methodology is its easy reproducibility, since the designed control loop does not require the mathematical model of the UAV. The tests were performed using the Gazebo simulator. The outcomes demonstrated that the proposed type-2 fuzzy variant displayed lower error values for both stabilization tests (keeping the UAV centered and oriented with the lines) and the following step in which the trajectory is time-variant, compared to the analogous T1_PID control and a classical PID controller tuned by the Zigler–Nichols method.

Funder

Institute CEFET/RJ

the federal Brazilian research agencies CAPES and CNPq

Rio de Janeiro research agency FAPERJ

Publisher

MDPI AG

Subject

Artificial Intelligence,Control and Optimization,Mechanical Engineering

Cited by 1 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. A Survey on UAV Applications in Smart City Management: Challenges, Advances, and Opportunities;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023

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