Delay-feedback-based recoil control for deepwater drilling riser systems

Abstract

This paper deals with the dynamic modelling and pure delayed $H_{\mathrm{\infty }}$ control for a deepwater drilling riser system in the presence of the friction force of seawater and drilling discharge mud. First, by simplifying a drilling riser system as a spring-mass-damping unit with three degrees of freedom, an increment equation of the riser system subject to friction force of seawater and drilling discharge mud is established. Then, by artificially introducing a time-varying delay with given lower and upper bounds into the control channel, a pure delayed $H_{\mathrm{\infty }}$ control scheme is presented to restrain the recoil responses of the riser system. Based on the Lyapunov–Krasovskii functional approach, several new sufficient conditions are derived to design the pure delayed $H_{\mathrm{\infty }}$ controller. Finally, comparative simulation results are given to show the effectiveness and merits of the proposed control scheme. It is demonstrated that to mitigate recoil response of the deepwater riser in the event of emergency disconnection, the proposed pure delayed $H_{\mathrm{\infty }}$ controllers are more economic than the delay-free $H_{\mathrm{\infty }}$ controller.

Keywords:

• Riser
• recoil control
• offshore platform
• time-delays

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

All data presented in this paper are freely available upon request.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 61773356].

Notes on contributors

Yan-Dong Zhao

Yan-Dong Zhao received the Ph.D. degree in Physical Oceanography from Ocean University of China, Qingdao, China, in 2006. She is currently an Associate Professor with College of Automation and Electronic Engineering, Qingdao University of Science & Technology, Qingdao. Her current research interests include process control and optimisation, and time-delay systems.

Yue-Ting Sun

Yue-Ting Sun is currently a Master degree candidate with Qingdao University of Science & Technology, Qingdao, China. Her current research interests include optimal control and modelling of industrial process control system.

Bao-Lin Zhang

Bao-Lin Zhang received the Ph.D. degree in physical oceanography from the Ocean University of China, Qingdao, China, in 2006. He is currently a professor with College of Automation and Electronic Engineering, Qingdao University of Science & Technology, Qingdao. His current research interests include network-based control systems, time-delay systems and vibration control systems.

Dawei Zhang

Dawei Zhang received the Ph.D. degree in Computer Science from Central Queensland University, Rockhampton, QLD, Australia, in 2012. He is currently a research fellow (associate professor level) with the School of Mathematics, Shandong University, China. His current research interests include network-based secure estimation and control, and vehicle control.