Analyzing of influencing factors on dynamic response characteristics of double closed-loop control digital hydraulic cylinder

Xia, Yimin; Shi, Yupeng; Yuan, Ye; Zhang, Yumin; Yao, Zhiwei

doi:10.1299/jamdsm.2019jamdsm0048

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…The reaching law is consistent with the previously used exponential reaching law based on the hyperbolic tangent function, based on the combined Equations ( 35), (39) and (40). The expression of the sliding mode synchronous controller of the hydraulic cylinder 2 is…”

Section: Synchronous Controller Designsupporting

confidence: 73%

“…The aforementioned study indicates that the use of closed-loop control is often employed inside hydraulic synchronization control systems to enhance the precision of those systems. The synchronization precision and stability of the hydraulic synchronous control system may be greatly increased by the controller by outputting the signal adjustment amount to compensate for the hydraulic system's synchronization error [38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cross-Coupled Sliding Mode Synchronous Control for a Double Lifting Point Hydraulic Hoist

Sun,

Dong,

2023

Sensors

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This paper proposes a sliding mode synchronous control approach to enhance the position synchronization performance and anti-interference capability of a double lifting point hydraulic hoist. Building upon the cross-coupling synchronous control method, a coupling sliding mode surface is formulated, incorporating the single-cylinder following error and double-cylinder synchronization error. Additionally, a sliding mode synchronous controller is devised to ensure the convergence of both the single-cylinder following and synchronization error. The hyperbolic tangent function is introduced to reduce the single-cylinder following error and the buffeting of the double-cylinder synchronization error curve under sliding mode synchronous control. The simulation results show that the synchronization accuracy of the sliding mode cross-coupling synchronization control in the initial stage of the system is 53.1% higher than that of the Proportional-Derivative (PD) cross-coupling synchronization, and the synchronization accuracy in the steady state of the system is improved by 90%. The designed synchronous controller has better performance under external disturbances.

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Section: Synchronous Controller Designsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Cross-Coupled Sliding Mode Synchronous Control for a Double Lifting Point Hydraulic Hoist

Sun,

Dong,

2023

Sensors

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show abstract

“…However, the information contained in the 350 feature parameters collected for each tool path may not be directly related to tool wear or may exhibit weak correlations. Therefore, this study employs the Pearson correlation coefficient method (Xia et al, 2019) to conduct preliminary feature selection. This helps reduce unnecessary computational burden and improves the convergence speed of the model.…”

Section: Feature Selectionmentioning

confidence: 99%

Tool state prediction model of Tent-ASO-BP neural network based on multi-feature fusion

ZHAO,

FAN,

TAN

et al. 2023

JAMDSM

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Aiming at the problem of tool wear prediction under small samples, this study proposes a tool condition prediction model based on the Tent-ASO-BP neural network. Firstly, the collected vibration and cutting force signals are denoised, and time-domain, frequency-domain, and time-frequency-domain feature parameters are extracted using techniques like fast Fourier transform and wavelet packet decomposition. Subsequently, based on the principle that tool wear increases with the number of cutting passes, Pearson correlation analysis is applied to select feature parameters with a correlation coefficient of no less than 0.9, indicating a strong correlation with tool wear. Finally, the selected feature parameters are combined into a feature vector, which serves as input for training the Tent-ASO-BP neural network for tool condition prediction. Experimental results demonstrate that the combined approach of Pearson correlation analysis and Tent-ASO-BP neural network exhibits excellent learning capability, enabling effective prediction of tool wear in small sample scenarios. This study contributes to addressing the challenges of tool wear prediction in situations with limited data. By incorporating denoising techniques and extracting relevant feature parameters, the proposed model enhances the accuracy of tool wear prediction. The utilization of Pearson correlation analysis ensures the selection of highly correlated features, further improving the model's performance. The Tent-ASO-BP neural network demonstrates its potential as a reliable tool for predicting tool wear, making it suitable for practical applications. In summary, this study presents a tool condition prediction model based on the Tent-ASO-BP neural network and Pearson correlation analysis, specifically designed for small sample scenarios. The experimental results confirm the model's excellent learning capability and its effectiveness in accurately predicting tool wear under such conditions.

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“…Hydraulic systems are typically classified into either open-loop or closed-loop circuits. Studies on valve-controlled open-loop systems have shown problems of pressure drops and leakages at control valves, resulting in energy wastage [1][2][3]. On the other hand, closed-loop circuits offer increased transmission efficiency by eliminating the need for directional control valves.…”

Section: Introductionmentioning

confidence: 99%

Development of an Adaptive Fuzzy Sliding Mode Controller of an Electrohydraulic Actuator Based on a Virtual Prototyping

2023

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The EHA (electro hydraulic actuator) has a notable advantage over conventional hydraulic actuators as it uses a closed-loop circuit, reducing the size and volume of oil, and eliminates pressure losses caused by valve orifices. However, accurate control performance of EHA is difficult to achieve using a traditional PID (proportional integral derivative) controller due to the strongly nonlinear, time-varying, and unknown dynamics of the system. Hence this paper seeks to address this problem by proposing a design of an intelligent controller for the EHA. The proposed adaptive fuzzy sliding mode controller (AFSMC) is developed as a hybrid of the adaptive, fuzzy logic, and sliding mode algorithms. To reduce costs and time, a virtual prototype approach is also proposed instead of experimentations to evaluate the performance of the proposed controller. The virtual model of the EHA is built in Amesime software, and then embedded into Matlab/Simulink where the AFSMC is developed and tested to obtain the position responses of the EHA. The results show that the AFSMC is highly successful and more efficient than the traditional PID at controlling the position of the piston accurately.

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Analyzing of influencing factors on dynamic response characteristics of double closed-loop control digital hydraulic cylinder

Cited by 4 publications

References 11 publications

Cross-Coupled Sliding Mode Synchronous Control for a Double Lifting Point Hydraulic Hoist

Cross-Coupled Sliding Mode Synchronous Control for a Double Lifting Point Hydraulic Hoist

Tool state prediction model of Tent-ASO-BP neural network based on multi-feature fusion

Development of an Adaptive Fuzzy Sliding Mode Controller of an Electrohydraulic Actuator Based on a Virtual Prototyping

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