Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network
The proposed research addresses the optimization challenges in servo motor control for pipe-cutting machines, aiming to enhance performance and efficiency. Recognizing the existing limitations in parameter optimization and system behavior prediction, a novel hybrid approach is introduced. The method...
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| Format: | Article |
| Language: | English |
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AIMS Press
2024-02-01
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| Series: | AIMS Electronics and Electrical Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/electreng.2024001 |
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| author | Santosh Prabhakar Agnihotri Mandar Padmakar Joshi |
| author_facet | Santosh Prabhakar Agnihotri Mandar Padmakar Joshi |
| author_sort | Santosh Prabhakar Agnihotri |
| collection | DOAJ |
| description | The proposed research addresses the optimization challenges in servo motor control for pipe-cutting machines, aiming to enhance performance and efficiency. Recognizing the existing limitations in parameter optimization and system behavior prediction, a novel hybrid approach is introduced. The methodology combines a Dandelion optimizer algorithm (DOA) for servo motor parameter optimization and an Attention pyramid convolution neural network (APCNN) (APCNN) for system behavior prediction. Integrated with a Programmable Logic Controller (PLC) and human-machine interface (HMI), this approach offers a comprehensive solution. Our research identifies a significant research gap in the efficiency of existing methods, emphasizing the need for improved control parameter optimization and system behavior prediction for cost reduction and enhanced efficiency. Through implementation on the MATLAB platform, the proposed DOA-APCNN approach demonstrates a noteworthy 30% reduction in computation time compared to existing methods such as Heap-based optimizer (HBO), Cuckoo Search Algorithm (CSA), and Salp Swarm Algorithm (SSA). These findings pave the way for faster and more efficient pipe-cutting operations, contributing to advancements in industrial automation and control systems. |
| format | Article |
| id | doaj-art-fdf1e81c7d784387b459802e8f2b67cd |
| institution | Kabale University |
| issn | 2578-1588 |
| language | English |
| publishDate | 2024-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Electronics and Electrical Engineering |
| spelling | doaj-art-fdf1e81c7d784387b459802e8f2b67cd2025-01-24T01:10:21ZengAIMS PressAIMS Electronics and Electrical Engineering2578-15882024-02-018112710.3934/electreng.2024001Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural networkSantosh Prabhakar Agnihotri0Mandar Padmakar Joshi1Department of Electronics and Telecommunication Engineering, GES R. H. Sapat College of Engineering Management studies and Research, Nasik, IndiaDepartment of Electronics and Telecommunication Engineering, GES R. H. Sapat College of Engineering Management studies and Research, Nasik, IndiaThe proposed research addresses the optimization challenges in servo motor control for pipe-cutting machines, aiming to enhance performance and efficiency. Recognizing the existing limitations in parameter optimization and system behavior prediction, a novel hybrid approach is introduced. The methodology combines a Dandelion optimizer algorithm (DOA) for servo motor parameter optimization and an Attention pyramid convolution neural network (APCNN) (APCNN) for system behavior prediction. Integrated with a Programmable Logic Controller (PLC) and human-machine interface (HMI), this approach offers a comprehensive solution. Our research identifies a significant research gap in the efficiency of existing methods, emphasizing the need for improved control parameter optimization and system behavior prediction for cost reduction and enhanced efficiency. Through implementation on the MATLAB platform, the proposed DOA-APCNN approach demonstrates a noteworthy 30% reduction in computation time compared to existing methods such as Heap-based optimizer (HBO), Cuckoo Search Algorithm (CSA), and Salp Swarm Algorithm (SSA). These findings pave the way for faster and more efficient pipe-cutting operations, contributing to advancements in industrial automation and control systems.https://www.aimspress.com/article/doi/10.3934/electreng.2024001cutting machinecircular sawservo motorspeed controlposition controlpipe lengthproximity sensor |
| spellingShingle | Santosh Prabhakar Agnihotri Mandar Padmakar Joshi Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network AIMS Electronics and Electrical Engineering cutting machine circular saw servo motor speed control position control pipe length proximity sensor |
| title | Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network |
| title_full | Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network |
| title_fullStr | Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network |
| title_full_unstemmed | Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network |
| title_short | Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network |
| title_sort | alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human machine interface using dandelion optimizer algorithm attention pyramid convolution neural network |
| topic | cutting machine circular saw servo motor speed control position control pipe length proximity sensor |
| url | https://www.aimspress.com/article/doi/10.3934/electreng.2024001 |
| work_keys_str_mv | AT santoshprabhakaragnihotri alternatingcurrentservomotorandprogrammablelogiccontrollercoupledwithapipecuttingmachinebasedonhumanmachineinterfaceusingdandelionoptimizeralgorithmattentionpyramidconvolutionneuralnetwork AT mandarpadmakarjoshi alternatingcurrentservomotorandprogrammablelogiccontrollercoupledwithapipecuttingmachinebasedonhumanmachineinterfaceusingdandelionoptimizeralgorithmattentionpyramidconvolutionneuralnetwork |