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Research on Pneumatic Control of a Pressurized Self-Elevating Mat for an Offshore Wind Power Installation Platform.
Cui, Junguo; Shi, Qi; Lin, Yunfei; Shi, Haibin; Yuan, Simin; Xiao, Wensheng.
Afiliación
  • Cui J; College of Mechanical and Electrical Engineering, China University of Petroleum, Qingdao 266580, China.
  • Shi Q; National Engineering Research Center of Marine Geophysical Prospecting and Exploration and Development Equipment, Qingdao 266580, China.
  • Lin Y; College of Mechanical and Electrical Engineering, China University of Petroleum, Qingdao 266580, China.
  • Shi H; National Engineering Research Center of Marine Geophysical Prospecting and Exploration and Development Equipment, Qingdao 266580, China.
  • Yuan S; College of Mechanical and Electrical Engineering, China University of Petroleum, Qingdao 266580, China.
  • Xiao W; National Engineering Research Center of Marine Geophysical Prospecting and Exploration and Development Equipment, Qingdao 266580, China.
Sensors (Basel) ; 23(24)2023 Dec 18.
Article en En | MEDLINE | ID: mdl-38139755
ABSTRACT
Efficient deep-water offshore wind power installation platforms with a pressurized self-elevating mat are a new type of equipment used for installing offshore wind turbines. However, the unstable internal pressure of the pressurized self-elevating mat can cause serious harm to the platform. This paper studies the pneumatic control system of the self-elevating mat to improve the precision of its pressure control. According to the pneumatic control system structure of the self-elevating mat, the pneumatic model of the self-elevating mat is established, and a conventional PID controller and fuzzy PID controller are designed and established. It can be seen via Simulink simulation that the fuzzy PID controller has a smaller adjustment time and overshoot, but its anti-interference ability is relatively weak. The membership degree and fuzzy rules of the fuzzy PID controller are optimized using a neural network algorithm, and a fuzzy neural network PID controller based on BP neural network optimization is proposed. The simulation results show that the overshoot of the optimized controller is reduced by 9.71% and the stability time is reduced by 68.9% compared with the fuzzy PID. Finally, the experiment verifies that the fuzzy neural network PID controller has a faster response speed and smaller overshoot, which improves the pressure control accuracy and robustness of the self-elevating mat and provides a scientific basis for the engineering applications of the self-elevating mat.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza