基于扩张状态观测器的滑动定向钻进轨迹跟踪模型预测控制

陆承达; 段炜涛; 吴加俊; 张幼振; 吴敏

doi:10.3799/dqkx.2026.117

Volume 51 Issue 8

Aug. 2026

Turn off MathJax

Article Contents

Article Navigation > Earth Science > 2026 > 51(8): 3017-3026

Lu Chengda, Duan Weitao, Wu Jiajun, Zhang Youzhen, Wu Min, 2026. Extended-State-Observer-Based Trajectory-Tracking Model Predictive Control for Sliding Directional Drilling. Earth Science, 51(8): 3017-3026. doi: 10.3799/dqkx.2026.117

Citation:

Lu Chengda, Duan Weitao, Wu Jiajun, Zhang Youzhen, Wu Min, 2026. Extended-State-Observer-Based Trajectory-Tracking Model Predictive Control for Sliding Directional Drilling. Earth Science, 51(8): 3017-3026. doi: 10.3799/dqkx.2026.117

Citation:

Lu Chengda, Duan Weitao, Wu Jiajun, Zhang Youzhen, Wu Min, 2026. Extended-State-Observer-Based Trajectory-Tracking Model Predictive Control for Sliding Directional Drilling. Earth Science, 51(8): 3017-3026. doi: 10.3799/dqkx.2026.117

PDF( 1609 KB)

Extended-State-Observer-Based Trajectory-Tracking Model Predictive Control for Sliding Directional Drilling

doi: 10.3799/dqkx.2026.117

Lu Chengda^{1, 3, 4
,
,},
Duan Weitao^{2, 3, 4},
Wu Jiajun^{2, 3, 4},
Zhang Youzhen⁵,
Wu Min^{1, 3, 4
,
,
,}

1.
School of Artificial Intelligence and Automation, China University of Geosciences (Wuhan), Wuhan 430074, China
2.
School of Future Technology, China University of Geosciences (Wuhan), Wuhan 430074, China
3.
Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China
4.
Engineering Research Center of Geo-Detection Intelligence Technology, Ministry of Education, Wuhan 430074, China
5.
CCTEG Xi'an Research Institute (Group) Co., Ltd., Xi'an 710077, China

Received Date: 2026-01-30
Publish Date: 2026-08-25

Abstract

Abstract

Sliding directional drilling is widely used in directional boreholes for tasks such as advance probing, detection of abnormal bodies related to geological hazards, and gas drainage, helping improve geological interpretation and drilling efficiency. This paper addresses the problem of reduced trajectory tracking accuracy caused by complex formation disturbances during sliding directional drilling, and proposes an extended-state-observer-based model predictive control method for trajectory tracking. First, the kinematic behavior of the drilling tool is analyzed and a trajectory extension model for sliding drilling is built. Based on this model, a trajectory prediction model is constructed, and an objective function that minimizes trajectory error is designed to develop the MPC controller. Then, to reduce steady tracking errors caused by formation disturbances, an extended state observer with disturbance estimation is designed to compensate the control input. Simulation results show that the proposed provides disturbance compensation, high tracking accuracy, and strong robustness, with practical value for improving exploration efficiency and reducing designed to operational risk.
- Sliding directional drilling,
- trajectory extension model,
- trajectory control,
- extended state observer,
- model predictive control

FullText(HTML)

References(19)

References

Basheer, A., Jeong, J. H., 2025. Coordinated Optimization of Wind Turbine Energy Capture Efficiency Using Model Predictive Control. International Journal of Electrical Power & Energy Systems, 172: 111361. https://doi.org/10.1016/j.ijepes.2025.111361

Bonzanini, A. D., Mesbah, A., Di Cairano, S., 2024. Perception-Aware Model Predictive Control for Constrained Control in Unknown Environments. Automatica, 160: 111418. https://doi.org/10.1016/j.automatica.2023.111418

Gurina, E., Klyuchnikov, N., Antipova, K., et al., 2022. Forecasting the Abnormal Events at Well Drilling with Machine Learning. Applied Intelligence, 52(9): 9980-9995. https://doi.org/10.1007/s10489-021-03013-x

Hong, L., Liu, H. T., Yang, Q. S., et al., 2024. Model Predictive Attitude Control of Unmanned Surface Vehicle Based on Short-Time Wave Prediction. Ocean Engineering, 314: 119727. https://doi.org/10.1016/j.oceaneng.2024.119727

Inyang, I. J., Whidborne, J. F., 2019. Bilinear Modelling, Control and Stability of Directional Drilling. Control Engineering Practice, 82: 161-172. https://doi.org/10.1016/j.conengprac.2018.10.008

Li, L., Wang, D. P., Chen, Z. C., et al., 2025. Trajectory-Tracking Control of Autonomous Vehicles with Dynamic Nonlinear Coupling Characteristics and Parameter Uncertainty. International Journal of Automotive Technology, 27(3): 1035-1049. https://doi.org/10.1007/s12239-025-00340-7

Mahdianfar, H., Hovakimyan, N., Pavlov, A., et al., 2016. L1 Adaptive Output Regulator Design with Application to Managed Pressure Drilling. Journal of Process Control, 42: 1-13. https://doi.org/10.1016/j.jprocont.2016.02.004

Panchal, N., Bayliss, M. T., Whidborne, J. F., 2010. Robust Linear Feedback Control of Attitude for Directional Drilling Tools (13th IFAC Symposium on Automation in Mining, Mineral and Metal Processing). IFAC Proceedings Volumes, 43(9): 92-97. https://doi.org/10.3182/20100802-3-ZA-2014.00022

Wan, M., Song, J. R., Wang, G. R., 2024. Observer-Based Adaptive Fuzzy Control of Stabilized Platform in Rotary Steerable System with Input Saturation and Output Constraint. Proceedings of the Institution of Mechanical Engineers, Part Ⅰ: Journal of Systems and Control Engineering, 238(10): 1785-1799. https://doi.org/10.1177/09596518241256144

Wang, G., Huang, W. J., Gao, D. L., 2023. Real-Time Control Algorithm of Well Trajectory for Push-the-Bit Rotary Steering Drilling System. SPE Journal, 28(5): 2148-2164. https://doi.org/10.2118/214703-pa

Zhang, C., Zou, W., Cheng, N. B., et al., 2018. Trajectory Tracking Control for Rotary Steerable Systems Using Interval Type-2 Fuzzy Logic and Reinforcement Learning. Journal of the Franklin Institute, 355(2): 803-826. https://doi.org/10.1016/j.jfranklin.2017.12.001

Zhao, W. Q., Wei, H. Q., Ai, Q., et al., 2024. Real-Time Model Predictive Control of Path-Following for Autonomous Vehicles towards Model Mismatch and Uncertainty. Control Engineering Practice, 153: 106126. https://doi.org/10.1016/j.conengprac.2024.106126

房培洪, 2024. 井下定向钻进技术在矿井地质勘探中的应用. 西部探矿工程, 36(11): 191-192, 195.

郭旭升, 2022. 我国陆上未来油气勘探领域探讨与攻关方向. 地球科学, 47(10): 3511-3523. doi: 10.3799/dqkx.2022.873

鞠玮, 肖宇航, 田永净, 等, 2025. 深部煤层气储层地质力学研究与进展. 地球科学. https://link.cnki.net/urlid/42.1874.P.20251230.1510.016.

李浩, 姚宁平, 陆承达, 等, 2025. 煤矿井下定向钻孔轨迹模型预测控制方法. 煤田地质与勘探, 53(2): 205-212.

秦永和, 2024. 滑动导向与旋转导向钻井技术进展及发展对策. 石油钻探技术, 52(6): 1-9.

闫燕强, 2025. 煤矿井下深孔定向钻进瓦斯抽采技术及应用. 西部探矿工程, 37(5): 133-134, 138.

杨金山, 卢伟涛, 孙青林, 等, 2025. 基于扩张状态观测器的翼伞系统滑模控制. 航天返回与遥感, 46(6): 14-24.

Relative Articles

Supplements(0)

Cited By

Proportional views