Vibration Control Research Of Oil Platform Based On DSPACE

When an ice sheet moves against a flexible vertical structure, it may fail either by buckling or by crushing. Then the structure may be destroyed by the ice force. As many oil platforms are to be erected at the oceans coved with ice, more and more problems appear. Since 1960s ice researcher had begun to study the problems of ice-structures interaction. In order to reduce the response of the platform vibration, some methods and devices must be found. To mitigation the ice-induced vibration of platform has been the first problem in Bohai bay.For complex, nonlinear structures, such as oil platforms, it is impossible to get the accurate models of the structures to be controlled and the external loadings. Although traditional control methods have many attractive features, they may run into problems when controlling systems that are difficult to model. This dissertation intends to introduce an intelligent active structural control strategy for oil platforms.The core of the paper is platform structure based on the artificial neural network control algorithm. Analysis in theory and simulation are employed to carry out the research. In this paper the artificial neural network control are introduced into structural control field, the intelligent control real-time simulational system for the platform structure model based on dSPACE is developed. The system adopted RCP (Rapid Control Prototyping) technology to control the platform structure model in real time.The paper creates mathematical models of adaptive truss snucturc and designs control method in MATLAB/Simulink environment based on MATLAB/dSPACE integrative simulation environment. The software/hardware system of dSPACE can provide actuators drive force and sensors' data collection so can realize half-physical simulation.The results on real-time simulational experiment verify that the major advantages of the artificial neural network control algorism include the quick and simple control without requiring exact models. The control algorism can obtain the perfect control effect. Comparing simulational results and experimental results, the validity of the numerical simulational method is proved. The study shows that the proposed active control strategy is effective and feasible, thus improving both service ability and survival.