摘要
导管架式海洋平台在随机波浪等外载荷作用下极易产生有害振动,且其动力响应具有极强的非线性和时变性,采用被动控制方法和基于精确数学模型的主动控制方法控制海洋平台的有害振动很难达到理想的控制效果。为此文中将灰预测和粗神经网络相结合,提出了一种基于灰预测和粗神经网络的预测逆控制方法,并将其与动态刚度阵法相结合用于导管架式海洋平台的振动主动控制中。数值算例分析表明此种控制方法可有效地控制波浪和风载荷作用而引起的导管架式平台的有害振动,并能解决由于控制信号传输等原因引起的时滞问题。
The offshore jacket platform usually produces harmful vibration under the action of random loads, and the corresponding dynamic response of the platform has severe nonlinearity and time variation. However, the ideal effects of vibration control can not be achieved using traditional passive control method or active control method based on the accurate mathematical model. In this paper, a new inverse control method is presented based on grey prediction, rough neural network and dynamic stiffness matrix, and which is applied to control the harmful vibration of the offshore jacket platform. Experimental results show that the new control method can effectively decrease the harmful vibration, and also successfully solve the control signal transmission delay problem.
出处
《船舶力学》
EI
北大核心
2010年第9期1008-1020,共13页
Journal of Ship Mechanics
关键词
导管架式海洋平台
灰预测
粗神经网络
逆控制
动态刚度阵法
offshore jacket platform
grey prediction
rough neural network
adaptive inverse control
dynamic stiffness matrix method
