During offshore exploration operations, vessels experience six degrees of freedom motion due to wind, waves, and currents. Among these motions, heave is particularly challenging to compensate for and significantly impacts the drilling process. This paper presents an active heave compensation control method for drill string systems in offshore exploration. To address parameter uncertainties, a single-neuron PID control approach based on a quadratic performance index is proposed. A simulation analysis was conducted using MATLAB software. The results demonstrate that the proposed controller provides smoother outputs than alternative controllers, highlighting its effectiveness in heave compensation.

1. [1] Q. He and P. Wang, “Current situation and prospect of deep-sea energy development,” Ocean Development and Management, Vol.34, No.12, pp. 66-71, 2017.
2. [2] L. Ma, Y.-L. Wang, and Q.-L. Han, “Event-triggered dynamic positioning for mass-switched unmanned marine vehicles in network environments,” IEEE Trans. on Cybernetics, Vol.52, No.5, pp. 3159-3171, 2020. https://doi.org/10.1109/TCYB.2020.3008998
3. [3] W. H. C. Sánchez, E. L. F. Fortaleza, A. B. Neto, and J. A. R. Vargas, “Effects of nonlinear friction of passive heave compensator on drilling operation—Part II: Active robust control,” Ocean Engineering, Vol.227, Article No.108837, 2021. https://doi.org/10.1016/j.oceaneng.2021.108837
4. [4] J. K. Woodacre, R. J. Bauer, and R. A. Irani, “A review of vertical motion heave compensation systems,” Ocean Engineering, Vol.104, pp. 140-154, 2015. https://doi.org/10.1016/j.oceaneng.2015.05.004
5. [5] B. Helian, C. Zheng, and B. Yao, “Energy-saving and accurate motion control of a hydraulic actuator with uncertain negative loads,” Chinese J. of Aeronautics, Vol.34, No.5, pp. 253-264, 2021. https://doi.org/10.1016/j.cja.2020.12.025
6. [6] F. Zhao, Y. Zhong, and Z. Fu, “Active and passive heave compensation system based on feedback linearization sliding mode variable structure control,” Ocean Engineering, Vol.305, Article No.117962, 2024. https://doi.org/10.1016/j.oceaneng.2024.117962
7. [7] Z. Xu, C. Sun, X. Hu, Q. Liu, and J. Yao, “Barrier Lyapunov function-based adaptive output feedback prescribed performance controller for hydraulic systems with uncertainties compensation,” IEEE Trans. on Industrial Electronics, Vol.70, No.12, pp. 12500-12510, 2023. https://doi.org/10.1109/TIE.2023.3236114
8. [8] W. Yang, S. Li, Z. Li, and X. Luo, “Highly accurate manipulator calibration via extended Kalman filter-incorporated residual neural network,” IEEE Trans. on Industrial Informatics, Vol.19, No.11, pp. 10831-10841, 2023. https://doi.org/10.1109/TII.2023.3241614
9. [9] Y. Zhang, Y. Sun, Z. Hu, B. Fang, Y. Xie, L. Chen, and Y. Teng, “Control performance analysis of mining ship heave compensation system based on fuzzy logic algorithm,” J. Européen des Systèmes Automatisés, Vol.55, No.2, pp. 213-220, 2022. https://doi.org/10.18280/jesa.550208
10. [10] X. Yan, F. Yan, D. Zhao, and S. Li, “Speed control of secondary regulation heave compensation based on fuzzy PID,” J. of Physics: Conf. Series, Vol.2419, No.1, Article No.012058, 2023. https://doi.org/10.1088/1742-6596/2419/1/012058
11. [11] L. Hu, M. Zhang, Z.-M. Yuan, H. Zheng, and W. Lv, “Predictive control of a heaving compensation system based on machine learning prediction algorithm,” J. of Marine Science and Engineering, Vol.11, No.4, Article No.821, 2023. https://doi.org/10.3390/jmse11040821
12. [12] P. Zhu, Q. Zhang, Z. Zhao, and B. Yang, “BP fuzzy neural network PID based constant tension control of traction winch,” Measurement and Control, Vol.56, Nos.3-4, pp. 857-873, 2023. https://doi.org/10.1177/00202940221094850
13. [13] J. Liu and X. Chen, “Adaptive control based on neural network and beetle antennae search algorithm for an active heave compensation system,” Int. J. of Control, Automation and Systems, Vol.20, No.2, pp. 515-525, 2022. https://doi.org/10.1007/s12555-020-0615-2
14. [14] J. Lei, H. Li, W. Tang, Y. Tian, Q. Yang, and S. Cao, “AMESim-based study on control method and simulation of drill string compensation system,” Chinese Hydraulics & Pneumatics, Vol.0, No.10, p. 83, 2019. https://doi.org/10.11832/j.issn.1000-4858.2019.10.014
15. [15] W. H. C. Sánchez, A. B. Neto, and E. L. F. Fortaleza, “Effects of nonlinear friction of passive heave compensator on drilling operation—Part I: Modeling and analysis,” Ocean Engineering, Vol.213, Article No.107743, 2020. https://doi.org/10.1016/j.oceaneng.2020.107743
16. [16] J. Xu, B. Yi, and Y. Zhan, “Review of heave compensation systems: Design and control strategies,” 2023 IEEE 11th Int. Conf. on Computer Science and Network Technology (ICCSNT), pp. 406-413. 2023. https://doi.org/10.1109/ICCSNT58790.2023.10334591
17. [17] T. Xu, Q. Liu, J. Dai, and W. Li, “Design and simulation analysis of new semi-active and multiplication process heave compensation device,” China Mechanical Engineering, Vol.27, No.5, p. 663, 2016.
18. [18] H. Li, J. Fu, S. Fan, T. Chen, P. Li, and W. Zheng, “Simulation on drill string compensation device based on heave prediction,” China Petroleum Machinery, Vol.49, No.3, pp. 57-64, 2021.
19. [19] F. Ding, W. Zhang, X. Luo, L. Hu, Z. Zhang, M. Wang, H. Li, M. Peng, X. Wu, L. Hu, and T. Zhang, “Gain self-adjusting single neuron PID control method and experiments for longitudinal relative position of harvester and transport vehicle,” Computers and Electronics in Agriculture, Vol.213, Article No.108215, 2023. https://doi.org/10.1016/j.compag.2023.108215
20. [20] P. Rezaei, H. P. Aria, and M. Ayati, “LQR based optimal passive fault-tolerant nonlinear fractional-order PID,” 2021 16th Int. Conf. on Engineering of Modern Electric Systems (EMES), pp. 1-4. 2021. https://doi.org/10.1109/EMES52337.2021.9484123