Automatic control system for the electric drive of an overhead crane considering elastic connections
DOI:
https://doi.org/10.15588/1607-6761-2024-3-3Keywords:
crane mechanisms, overhead crane, electric drive, automatic control system, adaptive system, elastic connectionsAbstract
Purpose. Investigation of the peculiarities of the automatic control system of an overhead crane electric drive with regard to elastic connections..
Research methods. To achieve this goal, we used the methods of system analysis and modeling with the help of software tools. This made it possible to reflect accurately the processes occurring in the system, as well as to test various operating scenarios and their impact on the overall system efficiency.
Results. The study considered the automatic control system of the electric drive and the importance of taking into account elastic connections. The proposed adaptive system uses the RBF neural network. The use of the proposed controller ensures resistance to disturbing influences and allows to level the load oscillations. The adaptability of the system is ensured by changing the parameters (load, speed of movement of mechanisms, stiffness, positioning accuracy, etc.) to meet the operating conditions of the overhead crane. Thanks to this, the system is able to operate efficiently even under variable loads and external influences. Computer modeling of the proposed control system was carried out, which confirmed its effectiveness under various operating conditions.
Scientific novelty.This system provides damping of load oscillations and increases the crane positioning accuracy. This is achieved by comparing it with existing control methods according to various criteria. It is proposed to use an algorithm for adapting the parameters of the control system in real time (load, trolley speed, cable length, mechanism stiffness, etc.), which significantly improves (by 5-7% positioning accuracy, by 8-10% stability) the performance of the system. In addition, the study confirmed the ability of the system to adapt to different operating conditions (changed load, variations in travel speed, uneven external disturbances), ensuring the stability and reliability of its operation, which is especially important for ensuring continuous operation of the crane in industrial environments.
Practical value. The use of this system can increase the overhead crane productivity by 5-10% compared to traditional control systems. Implementing the system in an industrial environment will significantly improve the efficiency and safety of the crane, as well as reduce maintenance and repair costs. In addition, this system can be used to modernize existing cranes, which will extend their service life and improve their reliability. This opens up new opportunities to improve the efficiency of industrial processes associated with the use of overhead cranes and provides better working conditions for operators.
References
Vydymysh A. A., Yaroshenko L.V. Fundamentals of Electric Drives. Theory and Practice. Part 1. / Text-book. Vinnytsia: VNAU, 2020. 387 p.
Zbitniev P.V., Budikov L.Yu., Aseev A.M. On the for-mation of braking processes in bridge cranes. Bulletin of the East Ukrainian National University named af-ter V. Dahl, 2013. №6 (195), part 2. P. 110-115.
Loveykin V.S., Romasevich Yu.O. Dynamic optimiza-tion of the motion regime of the crane transfer mechanism. Lifting and Transport Equipment, 2013. №3. P. 5-21.
Abdel-Rahman E. M., Nayfeh A. H., Masoud Z. N. Dynamics and control of cranes: A review. Journal of Vibration and Control, 2003. № 9(7). P. 863-908.
Zhao, X., & Huang, J. Distributed-mass payload dy-namics and control of dual cranes undergoing planar motions. Mechanical Systems and Signal Processing, 2019. 126. P. 636-648.
URL: https://doi.org/10.1016/j.ymssp.2019.02.032
Sun, Z., Bi, Y., Zhao, X., Sun, Z., Ying, C., Tan, S. Type-2 fuzzy sliding mode anti-swing controller de-sign and optimization for overhead crane, 2018. URL: https://doi.org/10.1109/access.2018.2869217
Wang, T., Tan, N., Zhang, X., et al. A time-varying sliding mode control method for distributed-mass double pendulum bridge crane with variable parameters, 2021.
URL: https://doi.org/10.1109/access.2021.3079303
Fihakhir, A. M., & Guerbouz, A. Intelligent control of industrial gantry crane model "3D Crane". Interna-tional Journal of Emerging Trends in Engineering Re-search (IJETER), 2022. 10(10). URL: https://doi.org/10.30534/ijeter/2022/0310102022
Wahyudi, Jalani, J., Muhida, R., & Salami, M. J. E. Control Strategy for Automatic Gantry Crane Sys-tems: A Practical and Intelligent Approach. Interna-tional Journal of Advanced Robotic Systems, 2007. 4(4). URL:
Abdullahi, A. M., Mohamed, Z., Selamat, H., Pota, H. R., Zainal Abidin, M. S., Ismail, F. S., & Haruna, A. Adaptive output-based command shaping for sway control of a 3D overhead crane with payload hoisting and wind disturbance, 2018. URL:
https://doi.org/10.30534/ijeter/2022/0310102022
Hmoumen, M., & Szabo, T. Controlling of payload swinging of an overhead crane. Robert Bosch De-partment of Mechatronics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Egyetemvaros, H-3515, Miskolc, Hungary. Published online December 13, 2021.
Carlos, W., Leite, F., Costa, G.A., Castro, I.L., Frank-lin, E., Ferreira, M., Moura, J.P., Viana, J., & Neto, D.F. Event Discrete Control Strategy Design of Over-head Crane embedded in Programmable Logic Con-troller, 2018. URL:
Klyuchem V.I. Theory of Electric Drives: Textbook for Universities, - 2nd ed., revised and supplemented. Energoatomizdat, 2001. 704 p.
Slepuzhnikov Ye.D., Fidrovskaya N.M., Varchenko I.S. Mechanisms for moving bridge cranes: mono-graph. Kharkiv: NUTZU, 2019. 124 p.
Volyanyuk V.O. Lifting and Transport Machines (Systems): Lecture Notes Part 1. Kyiv: KNUCA, 2019. 144 p.
Timoshenko, B. O., Filatov, S. Yu., Klimchenkov, A. G., Ivchenkov, M. V. Ways to improve the electro-mechanical system (EMS) of a bridge crane based on increasing the degree of automation. Scientific Bulle-tin of DGMA, 2016. № 3 (21E). P. 38. ISSN 2219-7869.
Alghanim, K. A., Alhazza, K. A., Masoud, Z. N. Dis-crete-time command profile for simultaneous travel and hoist maneuvers of overhead cranes. Journal of Sound and Vibration, 345, 2015. P. 47-57. URL: https://doi.org/10.1016/j.jsv.2015.01.042
Anh, L. V., & Linh, V. T. T. Position Control and Anti-Sway of Overhead Crane System with Uncertain Nonlinear Model. Faculty of Electrical Engineering, University of Economics – Technology for Industries, Ha Noi 100000, Vietnam, 2023.
Chen, H., Fang, Y., Sun, N. A swing constraint guaranteed MPC algorithm for underactuated overhead cranes. IEEE/ASME Transactions on Mechatronics, 2016. 21(5). P. 2543-2555.
URL: https://doi.org/10.1109/tmech.2016.2558202
Finch, J.W.; Giaouris, D. Controlled AC Electrical Drives. IEEE Trans. Ind. Electron. 2008, 55, P. 481–491. URL: https://doi.org/10.1556/606.2021.00474
Leite, D., Aguiar, C., Pereira, D., Souza, G., Škrjanc, I. Nonlinear fuzzy state-space modeling and LMI fuzzy control of overhead cranes. In 2019 IEEE In-ternational Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA, 2019. P. 1-6. URL: https://doi.org/10.1109/FUZZ-IEEE.2019.8858968
Pimkumwong, N.; Wang, M.-S. Online Speed Estima-tion Using Artificial Neural Network for Speed Sen-sorless Direct Torque Control of Induction Motor based on Constant V/F Control Technique. Energies, 2018. 11, 2176.
Urbas, A., Augustynek, K., & Stadnicki, J. Dynamics analysis of a crane with consideration of a load ge-ometry and a rope sling system. Journal of Sound and Vibration, 2024. 572, 118133. URL: https://doi.org/10.1016/j.jsv.2023.118133
Wu, X., Xu, K., Lei, M., He, X. Disturbance-compensation-based continuous sliding mode control for overhead cranes with disturbances. IEEE Transactions on Automation Science and Enginee-ring, 2020. 17(4). P. 2182-2189.
URL: https://doi.org/10.1109/tase.2020.3015870
Yang, C., Du, C., Liao, L. Design and implementation of finite time sliding mode controller for fuzzy over-head crane system. ISA Transactions, 2022. 124. P. 374-385.
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