{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:59:49Z","timestamp":1775145589105,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T00:00:00Z","timestamp":1681948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institute CEFET\/RJ","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"the federal Brazilian research agencies CAPES and CNPq","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"Rio de Janeiro research agency FAPERJ","award":["001"],"award-info":[{"award-number":["001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>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\u2013integral\u2013derivative) 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\u2013Nichols method.<\/jats:p>","DOI":"10.3390\/robotics12020060","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T02:05:31Z","timestamp":1682042731000},"page":"60","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["UAV Power Line Tracking Control Based on a Type-2 Fuzzy-PID Approach"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3672-0507","authenticated-orcid":false,"given":"Guilherme A. N.","family":"Pussente","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7458-8976","authenticated-orcid":false,"given":"Eduardo P.","family":"de Aguiar","sequence":"additional","affiliation":[{"name":"Department of Industrial and Mechanical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9171-3089","authenticated-orcid":false,"given":"Andre L. M.","family":"Marcato","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6916-700X","authenticated-orcid":false,"given":"Milena F.","family":"Pinto","sequence":"additional","affiliation":[{"name":"Federal Center of Technological Education of Rio de Janeiro (CEFET\/RJ), Rio de Janeiro 20271-110, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Pinto, M.F., Honorio, L.M., Melo, A., and Marcato, A.L. (2020). A robotic cognitive architecture for slope and dam inspections. Sensors, 20.","DOI":"10.3390\/s20164579"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Biundini, I.Z., Pinto, M.F., Melo, A.G., Marcato, A.L., Hon\u00f3rio, L.M., and Aguiar, M.J. (2021). A framework for coverage path planning optimization based on point cloud for structural inspection. Sensors, 21.","DOI":"10.3390\/s21020570"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Delavarpour, N., Koparan, C., Nowatzki, J., Bajwa, S., and Sun, X. (2021). A technical study on UAV characteristics for precision agriculture applications and associated practical challenges. Remote Sens., 13.","DOI":"10.3390\/rs13061204"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, H., Wang, L., Tian, T., and Yin, J. (2021). A review of unmanned aerial vehicle low-altitude remote sensing (UAV-LARS) use in agricultural monitoring in China. Remote Sens., 13.","DOI":"10.3390\/rs13061221"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.promfg.2021.10.026","article-title":"UAVs for Industrial Applications: Identifying Challenges and Opportunities from the Implementation Point of View","volume":"55","author":"Mourtzis","year":"2021","journal-title":"Procedia Manuf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/IOTM.0011.1900093","article-title":"AerialBlocks: Blockchain-enabled UAV virtualization for industrial IoT","volume":"4","author":"Pathak","year":"2021","journal-title":"IEEE Internet Things Mag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"030034","DOI":"10.1063\/5.0033989","article-title":"Comparative analysis of the impact of operating parameters on military and civil applications of mini unmanned aerial vehicle (UAV)","volume":"2311","author":"Ramesh","year":"2020","journal-title":"AIP Conf. Proc."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Utsav, A., Abhishek, A., Suraj, P., and Badhai, R.K. (2021, January 25\u201327). An IoT based UAV network for military applications. Proceedings of the 2021 Sixth International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India.","DOI":"10.1109\/WiSPNET51692.2021.9419470"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"73583","DOI":"10.1109\/ACCESS.2019.2919701","article-title":"Robust altitude stabilization of VTOL-UAV for payloads delivery","volume":"7","author":"Hedjar","year":"2019","journal-title":"IEEE Access"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"326","DOI":"10.3390\/futuretransp1020019","article-title":"Advances of UAVs toward future transportation: The State-of-the-Art, challenges, and Opportunities","volume":"1","author":"Gupta","year":"2021","journal-title":"Future Transp."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Almadhoun, R., Taha, T., Dias, J., Seneviratne, L., and Zweiri, Y. (2019, January 8\u201311). Coverage path planning for complex structures inspection using unmanned aerial vehicle (UAV). Proceedings of the International Conference on Intelligent Robotics and Applications, Shenyang, China.","DOI":"10.1007\/978-3-030-27541-9_21"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1394","DOI":"10.1016\/j.egyr.2022.07.115","article-title":"Electricity infrastructure inspection using AI and edge platform-based UAVs","volume":"8","author":"Lekidis","year":"2022","journal-title":"Energy Rep."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Krause, S., Sanders, T.G., Mund, J.P., and Greve, K. (2019). UAV-based photogrammetric tree height measurement for intensive forest monitoring. Remote Sens., 11.","DOI":"10.3390\/rs11070758"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"126958","DOI":"10.1016\/j.ufug.2020.126958","article-title":"Urban forest monitoring based on multiple features at the single tree scale by UAV","volume":"58","author":"Wang","year":"2021","journal-title":"Urban For. Urban Green."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"55817","DOI":"10.1109\/ACCESS.2019.2912306","article-title":"Lsar: Multi-uav collaboration for search and rescue missions","volume":"7","author":"Alotaibi","year":"2019","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Alsamhi, S.H., Shvetsov, A.V., Kumar, S., Shvetsova, S.V., Alhartomi, M.A., Hawbani, A., Rajput, N.S., Srivastava, S., Saif, A., and Nyangaresi, V.O. (2022). UAV computing-assisted search and rescue mission framework for disaster and harsh environment mitigation. Drones, 6.","DOI":"10.3390\/drones6070154"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1017\/S0263574720000521","article-title":"Arcog: An aerial robotics cognitive architecture","volume":"39","author":"Pinto","year":"2021","journal-title":"Robotica"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1080\/01431161.2019.1624858","article-title":"Cattle detection and counting in UAV images based on convolutional neural networks","volume":"41","author":"Shao","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","first-page":"100900","article-title":"Counting cattle in UAV images using convolutional neural network","volume":"29","author":"Matsubara","year":"2022","journal-title":"Remote. Sens. Appl. Soc. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1729881417752821","DOI":"10.1177\/1729881417752821","article-title":"Vision-based autonomous navigation approach for unmanned aerial vehicle transmission-line inspection","volume":"15","author":"Hui","year":"2018","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_21","first-page":"012023","article-title":"Electric Power Intelligent Inspection Robot: A Review","volume":"1750","author":"Zhang","year":"2021","journal-title":"J. Phys."},{"key":"ref_22","unstructured":"Silva, A.J.N.d. (2015). An\u00e1lise Organizacional de Acidentes de Trabalho no Setor de Distribui\u00e7\u00e3o de Energia el\u00e9trica. [Master\u2019s Thesis, Universidade Estadual Paulista Julio de Mesquita Filho]."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Takaya, K., Ohta, H., Kroumov, V., Shibayama, K., and Nakamura, M. (2019, January 9\u201311). Development of UAV system for autonomous power line inspection. Proceedings of the 2019 23rd International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania.","DOI":"10.1109\/ICSTCC.2019.8885596"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Men\u00e9ndez, O., P\u00e9rez, M., and Auat Cheein, F. (2019). Visual-based positioning of aerial maintenance platforms on overhead transmission lines. Appl. Sci., 9.","DOI":"10.3390\/app9010165"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1729881418763452","DOI":"10.1177\/1729881418763452","article-title":"Onboard visual-based navigation system for power line following with UAV","volume":"15","author":"Prieto","year":"2018","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3182","DOI":"10.1109\/TAES.2020.2967851","article-title":"Output-feedback image-based visual servoing for multirotor unmanned aerial vehicle line following","volume":"56","author":"Rafique","year":"2020","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_27","first-page":"403","article-title":"Airborne Computer System Path-Tracking Based Multi-PID-PSO Controller Design","volume":"14","author":"Abdullah","year":"2021","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"103722","DOI":"10.1016\/j.autcon.2021.103722","article-title":"Trajectory control of electro-hydraulic position servo system using improved PSO-PID controller","volume":"127","author":"Feng","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Takao\u011flu, F., Alshahrani, A., Ajlouni, N., Ajlouni, F., Al Kasasbah, B., and \u00d6zyava\u015f, A. (2022). Robust Nonlinear Non-Referenced Inertial Frame Multi-Stage PID Controller for Symmetrical Structured UAV. Symmetry, 14.","DOI":"10.3390\/sym14040689"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"So, G.B. (2021). A modified 2-DOF control framework and GA based intelligent tuning of PID controllers. Processes, 9.","DOI":"10.3390\/pr9030423"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1007\/s13369-020-04742-w","article-title":"Adaptive PID controller using sliding mode control approaches for quadrotor UAV attitude and position stabilization","volume":"46","author":"Noordin","year":"2021","journal-title":"Arab. J. Sci. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1007\/s11424-020-9306-6","article-title":"A second-order sliding mode controller of quad-rotor UAV based on PID sliding mode surface with unbalanced load","volume":"34","author":"Kang","year":"2021","journal-title":"J. Syst. Sci. Complex."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"38407","DOI":"10.1109\/ACCESS.2019.2906345","article-title":"Autonomous moving target-tracking for a UAV quadcopter based on fuzzy-PI","volume":"7","author":"Rabah","year":"2019","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Andrade, F.A., Guedes, I.P., Carvalho, G.F., Zachi, A.R., Haddad, D.B., Almeida, L.F., de Melo, A.G., and Pinto, M.F. (2021). Unmanned Aerial Vehicles Motion Control with Fuzzy Tuning of Cascaded-PID Gains. Machines, 10.","DOI":"10.3390\/machines10010012"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Carvalho, G., Guedes, I., Pinto, M., Zachi, A., Almeida, L., Andrade, F., and Melo, A.G. (2021, January 15\u201318). Hybrid PID-Fuzzy controller for autonomous UAV stabilization. Proceedings of the 2021 14th IEEE International Conference on Industry Applications (INDUSCON), Sao Paulo, Brazil.","DOI":"10.1109\/INDUSCON51756.2021.9529680"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Rao, J., Li, B., Zhang, Z., Chen, D., and Giernacki, W. (2022). Position Control of Quadrotor UAV Based on Cascade Fuzzy Neural Network. Energies, 15.","DOI":"10.3390\/en15051763"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"119520","DOI":"10.1109\/ACCESS.2021.3107906","article-title":"Self-learning in aerial robotics using type-2 fuzzy systems: Case study in hovering quadrotor flight control","volume":"9","author":"Santoso","year":"2021","journal-title":"IEEE Access"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Tavoosi, J., Shirkhani, M., Abdali, A., Mohammadzadeh, A., Nazari, M., Mobayen, S., Asad, J.H., and Bartoszewicz, A. (2021). A new general type-2 fuzzy predictive scheme for PID tuning. Appl. Sci., 11.","DOI":"10.3390\/app112110392"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"5069","DOI":"10.1109\/TIE.2017.2767546","article-title":"Type-2 fuzzy logic controllers made even simpler: From design to deployment for UAVs","volume":"65","author":"Sarabakha","year":"2017","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/0031-3203(91)90073-E","article-title":"A probabilistic Hough transform","volume":"24","author":"Kiryati","year":"1991","journal-title":"Pattern Recognit."},{"key":"ref_41","first-page":"923","article-title":"Enhanced karnik\u2013mendel algorithms","volume":"17","author":"Wu","year":"2008","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_42","unstructured":"Larson, K. (2016). Fuzzy Logic Tuning of a Proportional-Integral-Derivative Controller. [Master\u2019s Thesis, California State Polytechnic University]."},{"key":"ref_43","unstructured":"Haghrah, A.A., and Ghaemi, S. (2019). PyIT2FLS: A New Python Toolkit for Interval Type 2 Fuzzy Logic Systems. arXiv."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"9049","DOI":"10.1007\/s00500-022-07304-4","article-title":"Literature review on type-2 fuzzy set theory","volume":"26","author":"De","year":"2022","journal-title":"Soft Comput."}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/2\/60\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:20:08Z","timestamp":1760124008000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/2\/60"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,20]]},"references-count":44,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["robotics12020060"],"URL":"https:\/\/doi.org\/10.3390\/robotics12020060","relation":{},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,20]]}}}