2D balance control of a self-balancing robot for power inspection in urban networks

Autores

DOI:

https://doi.org/10.18265/1517-0306a2021id6839

Palavras-chave:

electric power transmission, power inspection, self-balancing robot, urban electric networks

Resumo

The power inspection of energy transmission networks is an effective way of mitigating risks, and failures, and avoiding mistakes in the transmission system. However, the inspection market is highly competitive and has difficulties in this process, mainly due to the high altitude of the lines. A standard solution for inspection of high-altitude power lines can be implemented using drones and aircraft, however, has a high cost for operation and poor logistics viability. In this scenario, "Prof. Raul Guenther’s Robotic Lab" developed a project of a robot that goes through low and medium-voltage wires to power inspection of transmission systems in urban networks. In this paper we propose the use of a self-balancing robot, aiming to execute the inspection, using a 2D balance control to stabilize the balance on the cable. Moreover, we evaluate the viability and effectiveness of the proposed control strategy, highlighting its advantages and properties using numerical simulations considering a non-linear model, and expected disturbances. Moreover, we develop computational experiments with graphical results, simulating the model in different situations to find the limits of the controller, based on the maximum speed of the wind and the robot moving through the wires.

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Referências

ADABO, G. J. Long range unmanned aircraft system for power line inspection of Brazilian electrical system. Journal of Energy and Power Engineering, v. 8, n. 2, p. 394-398, 2014. DOI: http://dx.doi.org/10.17265/1934-8975/2014.02.025.

AHMED, E. Q.; ALJAZAERY, I. A.; AL-ZUBIDI, A. F.; ALRIKABI, H. T. S. Design and implementation control system for a self-balancing robot based on internet of things by using Arduino microcontroller. Periodicals of Engineering and Natural Sciences, v. 9, n. 3, p. 409-417, 2021. DOI: http://dx.doi.org/10.21533/pen.v9i3.2178.

ALHASSAN, A. B.; ZHANG, X.; SHEN, H.; XU, H. Power transmission line inspection robots: a review, trends and challenges for future research. International Journal of Electrical Power & Energy Systems, v. 118, 105862, 2020. DOI: https://doi.org/10.1016/j.ijepes.2020.105862.

BARBOSA, L.; VELOSO, L. Consumption, domestic life and sustainability in Brazil. Journal of Cleaner Production, v. 63, p. 166-172, 2014. DOI: https://doi.org/10.1016/j.jclepro.2013.09.020.

BELASCUEN, G.; AGUILAR, N. Design, modeling and control of a reaction wheel balanced inverted pendulum. In: 2018 IEEE BIENNIAL CONGRESS OF ARGENTINA (ARGENCON), 2018, San Miguel de Tucuman. Proceedings [...]. San Miguel de Tucuman: IEEE, 2018. p. 1-9. DOI: https://doi.org/10.1109/ARGENCON.2018.8646093.

DOUKAS, H.; KARAKOSTA, C.; FLAMOS, A.; PSARRAS, J. Electric power transmission: An overview of associated burdens. International Journal of Energy Research, v. 35, n. 11, p. 979-988, 2011. DOI: https://doi.org/10.1002/er.1745.

DU, L.; ZHAO, Z.; PANG, C.; FANG, Z. Drag force micro solid state silicon plate wind velocity sensor. Sensors and Actuators A: Physical, v. 151, n. 1, p. 35-41, 2009. DOI: https://doi.org/10.1016/j.sna.2009.02.003.

GAO, T.; JIN, J.; HAO, X. A single-ball-driven self-balancing robot controller based on genetic algorithm optimization. In: INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND ADVANCED MANUFACTURE (AIAM2020), 2., 2020, Manchester. Proceedings […]. Manchester: ACM, 2020. p. 453-457. DOI: https://dx.doi.org/10.1145/3421766.3421789.

HAN, S.; HAO, R.; LEE, J. Inspection of insulators on high-voltage power transmission lines. IEEE Transactions on Power Delivery, v. 24, n. 4, p. 2319-2327, 2009. DOI: https://doi.org/10.1109/TPWRD.2009.2028534.

IRFAN, S.; MEHMOOD, A.; RAZZAQ, M. T.; IQBAL, J. Advanced sliding mode control techniques for inverted pendulum: modelling and simulation. Engineering Science and Technology, an International Journal, v. 21, n. 4, p. 753-759, 2018. DOI: https://doi.org/10.1016/j.jestch.2018.06.010.

JALAL, M. F. A.; SAHARI, K. S. M.; FEI, H. M.; LEONG, J. C. T. Design and development of three arms transmission line inspection robot. Journal of Robotics, Networking and Artificial Life, v. 5, n. 3, p. 157-160, 2018. DOI: https://doi.org/10.2991/jrnal.2018.5.3.3.

JMEL, I.; DIMASSI, H.; SAID, S. H.; M’SAHLI, F. Adaptive observer-based output feedback control for two-wheeled self-balancing robot. Mathematical Problems in Engineering, v. 2020, 5162172, 2020. DOI: https://doi.org/10.1155/2020/5162172.

KAYGUSUZ, K. Sustainable development of hydroelectric power. Energy Sources, v. 24, n. 9, p. 803-815, 2002. DOI: https://doi.org/10.1080/00908310290086725.

LEE, C.; AN, D. Reinforcement learning and neural network-based artificial intelligence control algorithm for self-balancing quadruped robot. Journal of Mechanical Science and Technology, v. 35, n. 1, p. 307-322, 2021. DOI: https://doi.org/10.1007/s12206-020-1230-0.

LUQUE-VEGA, L. F.; CASTILLO-TOLEDO, B.; LOUKIANOV, A.; GONZALEZ-JIMENEZ, L. E. Power line inspection via an unmanned aerial system based on the quadrotor helicopter. In: IEEE MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (MELECON 2014), 17., 2014, Beirut. Proceedings […]. Beirut: IEEE, 2014. p. 393-397. DOI: https://doi.org/10.1109/MELCON.2014.6820566.

NGUYEN, D.-M.; NGUYEN, V.-T.; NGUYEN, T.-T. A neural network combined with sliding mode controller for the two-wheel self-balancing robot. International Journal of Artificial Intelligence (IAES), v. 10, n. 3, p. 592-601, 2021. DOI: http://doi.org/10.11591/ijai.v10.i3.pp592-601.

OGATA, K. Modern control engineering. 5th ed. Upper Saddle River, NJ: Prentice Hall, 2010.

OLIVEIRA, N. C. C. A grande aceleração e a construção de barragens hidrelétricas no Brasil. Varia Historia, v. 34, n. 65, p. 315-346, 2018. DOI: https://doi.org/10.1590/0104-87752018000200003. In Portuguese.

OLSSON, H.; ÅSTRÖM, K. J.; WIT, C. C.; GÄFVERT, M.; LISCHINSKY, P. Friction models and friction compensation. European Journal of Control, v. 4, n. 3, p. 176-195, 1998. DOI: https://doi.org/10.1016/S0947-3580(98)70113-X.

RAIMUNDO, D. R.; SANTOS, I. F. S. Estudo de um projeto para geração de energia eólica no Brasil: viabilidade econômica e emissões evitadas. Revista Brasileira de Energias Renováveis, v. 4, n. 4, p. 65-75, 2015. DOI: http://dx.doi.org/10.5380/rber.v4i4.44156. In Portuguese.

ROUSSIALIAN, M.; AL-ZANBARAKJI, H.; KHAWAND, A.; RAHAL, A.; OWAYJAN, M. Design and development of a pipeline inspection robot. In: RIZK, R.; AWAD, M. (ed.). Mechanism, machine, robotics, and mechatronics sciences. Cham: Springer, 2019. p. 43-52. DOI: https://doi.org/10.1007/978-3-319-89911-4_4.

SANTOS, M. A urbanização brasileira. 1st ed. São Paulo: EdUSP, 2013. In Portuguese.

SHAIKAT, A. S.; HUSSEIN, M. R.; TASNIM, R. Design and development of a pipeline inspection robot for visual inspection and fault detection. In: PAN, I.; MUKHERJEE, A.; PIURI, V. (ed.). Proceedings of Research and Applications in Artificial Intelligence. Singapore: Springer, 2021. p. 243-253. DOI: https://doi.org/10.1007/978-981-16-1543-6_23.

SUN, C.; LU, T.; YUAN, K. Balance control of two-wheeled self-balancing robot based on linear quadratic regulator and neural network. In: INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP), 4., 2013, Beijing. Proceedings […]. Beijing: IEEE, 2013. p. 862-867. DOI: https://doi.org/10.1109/ICICIP.2013.6568193.

TRANSMOTEC. DC-motors 12VDC 6A 8400rpm 53W. Product-name: 770-7040-CC: Datasheet. 2021. Available at: https://www.transmotec.com/product/770-7040-cc/. Accessed on: 14 jun. 2022.

WANG, W.; HE, T.; WANG, H.; CHEN, W. Balance control of a novel power transmission line inspection robot. In: 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO), 2015, Zhuhai. Proceedings […]. Zhuhai: IEEE, 2015. p. 1882-1887. DOI: https://doi.org/10.1109/ROBIO.2015.7419047.

XIE, X.; LIU, Z.; XU, C.; ZHANG, Y. A multiple sensors platform method for power line inspection based on a large unmanned helicopter. Sensors, v. 17, n. 6, 1222, 2017. DOI: https://doi.org/10.3390/s17061222.

XUAN, H. L.; HOANG, Q.-D.; LEE, S.-G.; XUAN, D. P.; VIET, H. T.; VAN, M. P.; VAN, H. P.; VIET, H. P.; TUAN, P. D.; NGUYEN, D. A. Adaptive hierarchical sliding mode control using an artificial neural network for a ballbot system with uncertainties. Journal of Mechanical Science and Technology, v. 36, n. 2, p. 947-958, 2022. DOI: https://doi.org/10.1007/s12206-022-0141-7.

ZHANG, H. Y.; ZHU, S. L.; ZHANG, Y.; LOU, Q.; ZHANG, L. Research and implementation of condition-based maintenance technology system for power transmission and distribution equipments. Power System Technology, v. 33, n. 13, p. 70-73, 2009.

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Publicado

2024-04-10

Edição

Seção

Engenharias IV - Engenharia Elétrica - Sistemas de Controle, Automação e Robótica

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