Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer
The wet dual-clutch transmission (DCT) controls clutch engagement via a hydraulic actuator to facilitate smooth starting and gearshifts. The quality of these operations is directly influenced by the hydraulic actuator’s precision in pressure control. However, existing research has overloo...
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IEEE
2023-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/10288468/ |
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author | Yue Wang Han Shi Xiang Rong Dezhi Jiang |
author_facet | Yue Wang Han Shi Xiang Rong Dezhi Jiang |
author_sort | Yue Wang |
collection | DOAJ |
description | The wet dual-clutch transmission (DCT) controls clutch engagement via a hydraulic actuator to facilitate smooth starting and gearshifts. The quality of these operations is directly influenced by the hydraulic actuator’s precision in pressure control. However, existing research has overlooked that uncertainties, such as variations in the dynamic model parameters of the hydraulic actuator and modeling errors, can impact the effectiveness of pressure control. Furthermore, the intricate nonlinear characteristics of the hydraulic actuator pose significant challenges in designing an appropriate hydraulic controller. In response to these challenges, we propose an adaptive pressure control method for the hydraulic actuator, leveraging a T-S fuzzy model and an extended state observer. Firstly, a dynamic model is established for the clutch hydraulic actuator that comprehensively accounts for its nonlinear attributes. An extended state observer is then designed to estimate variables that are arduous to measure directly, including parameter fluctuations, modeling inaccuracies, and the state variables. Building upon this foundation, the T-S fuzzy modeling technique is employed to approximate the nonlinear components embedded within the dynamic model, and the backstepping method is employed to design an adaptive pressure controller for the hydraulic actuator. Simulation verification results demonstrate the efficacy and robustness of the adaptive pressure control method in addressing parameter fluctuations and other pertinent factors. |
first_indexed | 2024-03-09T15:41:44Z |
format | Article |
id | doaj.art-54afab17e3364b4fb3d5cd0769750d2c |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-03-09T15:41:44Z |
publishDate | 2023-01-01 |
publisher | IEEE |
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series | IEEE Access |
spelling | doaj.art-54afab17e3364b4fb3d5cd0769750d2c2023-11-25T00:01:10ZengIEEEIEEE Access2169-35362023-01-011112909012909910.1109/ACCESS.2023.332633810288468Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State ObserverYue Wang0https://orcid.org/0009-0008-0690-0399Han Shi1Xiang Rong2Dezhi Jiang3CCTEG Changzhou Research Institute, Changzhou, ChinaCCTEG Changzhou Research Institute, Changzhou, ChinaCCTEG Changzhou Research Institute, Changzhou, ChinaCCTEG Changzhou Research Institute, Changzhou, ChinaThe wet dual-clutch transmission (DCT) controls clutch engagement via a hydraulic actuator to facilitate smooth starting and gearshifts. The quality of these operations is directly influenced by the hydraulic actuator’s precision in pressure control. However, existing research has overlooked that uncertainties, such as variations in the dynamic model parameters of the hydraulic actuator and modeling errors, can impact the effectiveness of pressure control. Furthermore, the intricate nonlinear characteristics of the hydraulic actuator pose significant challenges in designing an appropriate hydraulic controller. In response to these challenges, we propose an adaptive pressure control method for the hydraulic actuator, leveraging a T-S fuzzy model and an extended state observer. Firstly, a dynamic model is established for the clutch hydraulic actuator that comprehensively accounts for its nonlinear attributes. An extended state observer is then designed to estimate variables that are arduous to measure directly, including parameter fluctuations, modeling inaccuracies, and the state variables. Building upon this foundation, the T-S fuzzy modeling technique is employed to approximate the nonlinear components embedded within the dynamic model, and the backstepping method is employed to design an adaptive pressure controller for the hydraulic actuator. Simulation verification results demonstrate the efficacy and robustness of the adaptive pressure control method in addressing parameter fluctuations and other pertinent factors.https://ieeexplore.ieee.org/document/10288468/Hydraulic actuatoradaptive pressure controlT-S fuzzy modelextended state observer |
spellingShingle | Yue Wang Han Shi Xiang Rong Dezhi Jiang Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer IEEE Access Hydraulic actuator adaptive pressure control T-S fuzzy model extended state observer |
title | Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer |
title_full | Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer |
title_fullStr | Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer |
title_full_unstemmed | Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer |
title_short | Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer |
title_sort | adaptive pressure control of the clutch hydraulic actuator in wet dual clutch transmission based on t s fuzzy model and extended state observer |
topic | Hydraulic actuator adaptive pressure control T-S fuzzy model extended state observer |
url | https://ieeexplore.ieee.org/document/10288468/ |
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