ESTIMATION OF RESIDUAL PAYLOAD SWING AMPLITUDE FOR AUTOMATED CRANE UNITS SUBJECTED TO INACCURATE CABLE LENGTH VALUE

D. V. Bazhutin, V. N. Pavlysh

About the authors

D. V. Bazhutin, V. N. Pavlysh

Бажутин Денис Владимирович – старший преподаватель кафедры электропривода и автоматизации промышленных установок», Федеральное государственное бюджетное образовательное учреждение «Донецкий национальный технический университет», г. Донецк. Область научных интересов: микропроцессорные системы автоматическог о управления электроприводами, робототехника, адрес 283 112, г. Донецк, ул. Туполева, дом 26, квартира 68.

Павлыш Владимир Николаевич – заведующий кафедрой прикладной математики и искусственного интеллекта, Федеральное государственное бюджетное образовательное учреждение «Донецкий национальный технический университет», г. Донецк. Область научных интересов: математическое моделирование и управление процессами в сложных динамических системах.

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UDC: 519.4
DOI: 10.24412/2413-7383-2025-2-37-106-115
Language: Russian

Abstract: The paper considers the problem of improving the payload swing elimination algorithms for gantry cranes implementing stepwise acceleration diagrams for horizontal motion electric drives. The analysis inaccurate cable length estimation effect on the accuracy of three-stage payload swing elimination algorithm for gantry crane automated motion control systems is given. The analytical dependencies of amplitude and starting phase of payload residual sway from relative cable length estimation error and electric drive acceleration parameters were derived. The correctness of obtained results was confirmed via computer simulation.

Keywords: gantry crane, anti-swing control, three-stage acceleration diagram, residual sway, computer simulation.

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Issue: 2(37)'2025
Section: AUTOMATION AND CONTROL OF TECHNOLOGICAL PROCESSES AND PRODUCTION
How to cite: D. V. Bazhutin, V. N. Pavlysh. ESTIMATION OF RESIDUAL PAYLOAD SWING AMPLITUDE FOR AUTOMATED CRANE UNITS SUBJECTED TO INACCURATE CABLE LENGTH VALUE // Problems of Artificial Intelligence. - 2025. - № 2 (37). - P. 106-115. - https://paijournal.guiaidn.ru/en/2025/2(37)-10.html

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