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论文类型：期刊论文

发表时间：2009-06-01

发表刊物：CHINA OCEAN ENGINEERING

收录刊物：SCIE、EI、ISTIC、Scopus

卷号：23

期号：2

页面范围：185-198

ISSN号：0890-5487

关键字：offshore jacket platform; rough set; neural network; dynamic stiffness matrix; adaptive predictive inverse control; wave load; wind load

摘要：The offshore jacket platform is a complex and time-varying nonlinear system, which can be excited of harmful vibration by external loads. It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model. In this paper, an adaptive inverse control method is proposed on the basis of novel rough neural networks (RNN) to control the harmful vibration of the offshore jacket platform, and the offshore jacket platform model is established by dynamic stiffness matrix (DSM) method. Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory, RNN is utilized to identify the predictive inverse model of the offshore jacket platform system. Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads, and to deal with the delay problem caused by signal transmission in the control process. The numerical results show that the constructed novel RNN has advantages such as clear structure, fast training speed and strong error-tolerance ability, and the proposed method based on RNN can effectively control the harmful vibration of the offshore jacket platform.