Automatic control system for the electric drive of an overhead crane considering elastic connections

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.

Publication Details

Journal
The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Published
2024-10-30
Primary Topic
Dynamics and Control of Mechanical Systems
Type
article
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article

Automatic control system for the electric drive of an overhead crane considering elastic connections

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Dynamics and Control of Mechanical Systems
article

Automatic control system for the electric drive of an overhead crane considering elastic connections

article en

Abstract

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.

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Industry, innovation and infrastructure
Openalex Percentile: Top 55%
Dynamics and Control of Mechanical Systems
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