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Article

A Distributed Parameter Identification Method for Tractor Electro-Hydraulic Hitch Systems Based on Dual-Mode Grey-Box Modelling

1
College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
2
College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou 239000, China
*
Author to whom correspondence should be addressed.
Processes 2025, 13(11), 3608; https://doi.org/10.3390/pr13113608
Submission received: 21 October 2025 / Revised: 5 November 2025 / Accepted: 6 November 2025 / Published: 7 November 2025
(This article belongs to the Section Automation Control Systems)

Abstract

To address the pronounced asymmetry and strong nonlinearity exhibited by the tractor electro-hydraulic hitch system during lifting and lowering operations, this study proposes a distributed parameter identification method based on a dual-mode grey-box modelling approach. Following a mode decomposition strategy, the lifting and lowering processes are regarded as two independent subsystems. Benchmark transfer function models are established for each subsystem through theoretical derivation. Considering the nonlinear characteristics and unmodeled dynamics that cannot be accurately captured by the benchmark model, a long short-term memory (LSTM) neural network compensator is introduced to enhance the model performance. Ultimately, a series-compensated dual-channel grey-box model is established, which effectively integrates mechanistic interpretability with high modelling accuracy. Then, to cope with the high-dimensional and heterogeneous parameter space of the constructed grey-box structure, a distributed parameter identification framework is proposed. This framework employs a staged optimization process that combines the whale optimization algorithm (WOA) with the gradient descent (GD) method to efficiently identify the hybrid parameter set. The identified models are validated through bench experiments. The results show that the proposed grey-box models achieve root mean square errors (RMSEs) of 0.33 mm and 0.48 mm, and mean absolute errors (MAEs) of 0.24 mm and 0.40 mm for the lifting and lowering processes, respectively. Compared with a single transfer function model, the RMSE is reduced by 57.6% and 87.3%, and the MAE is reduced by 59.2% and 87.9%, respectively. The proposed method substantially improves the modelling accuracy of the electro-hydraulic hitch system, providing a reliable foundation for system characterization and the design of high-performance control strategies for tractor electro-hydraulic hitch systems.
Keywords: tractor; electro-hydraulic hitch system; dual-mode; grey-box modelling; parameter identification tractor; electro-hydraulic hitch system; dual-mode; grey-box modelling; parameter identification

Share and Cite

MDPI and ACS Style

Sun, X.; Pan, S.; Song, Y.; Jiang, C.; Lu, Z. A Distributed Parameter Identification Method for Tractor Electro-Hydraulic Hitch Systems Based on Dual-Mode Grey-Box Modelling. Processes 2025, 13, 3608. https://doi.org/10.3390/pr13113608

AMA Style

Sun X, Pan S, Song Y, Jiang C, Lu Z. A Distributed Parameter Identification Method for Tractor Electro-Hydraulic Hitch Systems Based on Dual-Mode Grey-Box Modelling. Processes. 2025; 13(11):3608. https://doi.org/10.3390/pr13113608

Chicago/Turabian Style

Sun, Xiaoxu, Siwei Pan, Yue Song, Chunxia Jiang, and Zhixiong Lu. 2025. "A Distributed Parameter Identification Method for Tractor Electro-Hydraulic Hitch Systems Based on Dual-Mode Grey-Box Modelling" Processes 13, no. 11: 3608. https://doi.org/10.3390/pr13113608

APA Style

Sun, X., Pan, S., Song, Y., Jiang, C., & Lu, Z. (2025). A Distributed Parameter Identification Method for Tractor Electro-Hydraulic Hitch Systems Based on Dual-Mode Grey-Box Modelling. Processes, 13(11), 3608. https://doi.org/10.3390/pr13113608

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