DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED
ABSTRACT To enhance the automation and efficiency of combine harvesters, this paper proposes a predictive control method based on Long Short-Term Memory (LSTM) neural networks. The method integrates multi-sensor data fusion using an Extended Kalman Filter (EKF) to improve speed measurement accuracy....
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| Format: | Article |
| Language: | English |
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Sociedade Brasileira de Engenharia Agrícola
2025-06-01
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| Series: | Engenharia Agrícola |
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| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162025000100315&lng=en&tlng=en |
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| _version_ | 1849696428952125440 |
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| author | Jin Chen Jiaqi Ji Kuizhou Ji Yuhang Chen |
| author_facet | Jin Chen Jiaqi Ji Kuizhou Ji Yuhang Chen |
| author_sort | Jin Chen |
| collection | DOAJ |
| description | ABSTRACT To enhance the automation and efficiency of combine harvesters, this paper proposes a predictive control method based on Long Short-Term Memory (LSTM) neural networks. The method integrates multi-sensor data fusion using an Extended Kalman Filter (EKF) to improve speed measurement accuracy. By considering feeding volume, operational performance indicators, and critical component speeds, an LSTM-based model predicts the optimal operation speed. The predicted speed is then regulated through an incremental proportional-integral-derivative (PID) control control system. Simulation and field experiments validate the effectiveness of the proposed approach, demonstrating improved speed stability and work efficiency. The results indicate that the system enhances operational performance and reduces manual intervention, contributing to the advancement of intelligent agricultural machinery. |
| format | Article |
| id | doaj-art-59b8d5d73faf4641b8d35c8da69fe001 |
| institution | DOAJ |
| issn | 0100-6916 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Sociedade Brasileira de Engenharia Agrícola |
| record_format | Article |
| series | Engenharia Agrícola |
| spelling | doaj-art-59b8d5d73faf4641b8d35c8da69fe0012025-08-20T03:19:28ZengSociedade Brasileira de Engenharia AgrícolaEngenharia Agrícola0100-69162025-06-014510.1590/1809-4430-eng.agric.v45e20240150/2025DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEEDJin Chenhttps://orcid.org/0009-0008-5847-9890Jiaqi JiKuizhou JiYuhang ChenABSTRACT To enhance the automation and efficiency of combine harvesters, this paper proposes a predictive control method based on Long Short-Term Memory (LSTM) neural networks. The method integrates multi-sensor data fusion using an Extended Kalman Filter (EKF) to improve speed measurement accuracy. By considering feeding volume, operational performance indicators, and critical component speeds, an LSTM-based model predicts the optimal operation speed. The predicted speed is then regulated through an incremental proportional-integral-derivative (PID) control control system. Simulation and field experiments validate the effectiveness of the proposed approach, demonstrating improved speed stability and work efficiency. The results indicate that the system enhances operational performance and reduces manual intervention, contributing to the advancement of intelligent agricultural machinery.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162025000100315&lng=en&tlng=enharvesting automationPID control optimizationLSTM neural networkmulti-sensor fusionsmart agricultural machinery |
| spellingShingle | Jin Chen Jiaqi Ji Kuizhou Ji Yuhang Chen DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED Engenharia Agrícola harvesting automation PID control optimization LSTM neural network multi-sensor fusion smart agricultural machinery |
| title | DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED |
| title_full | DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED |
| title_fullStr | DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED |
| title_full_unstemmed | DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED |
| title_short | DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED |
| title_sort | deep learning driven predictive control method for optimizing combine harvester operation speed |
| topic | harvesting automation PID control optimization LSTM neural network multi-sensor fusion smart agricultural machinery |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162025000100315&lng=en&tlng=en |
| work_keys_str_mv | AT jinchen deeplearningdrivenpredictivecontrolmethodforoptimizingcombineharvesteroperationspeed AT jiaqiji deeplearningdrivenpredictivecontrolmethodforoptimizingcombineharvesteroperationspeed AT kuizhouji deeplearningdrivenpredictivecontrolmethodforoptimizingcombineharvesteroperationspeed AT yuhangchen deeplearningdrivenpredictivecontrolmethodforoptimizingcombineharvesteroperationspeed |