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作 者:杨青[1] David Davies
机构地区:[1]西南石油大学电气信息学院,四川成都610500 [2]Institute of Petroleum Engineering,Heriot-Watt University,Edinburgh,UK,EH14 4AS
出 处:《控制工程》2013年第3期489-492,496,共5页Control Engineering of China
基 金:国家自然科学基金青年基金项目(51204139);四川省教育厅重点项目(11ZA023)
摘 要:随着石油开采中出现的新技术——智能井的应用,井控由地面转移到地下。为了解决地层物理属性难以准确获得以及流体流动的强非线性给井下控制带来的困难,研究了带有模型不确定性的非线性预测控制器。首先建立了带有不确定性的预测控制模型;然后基于反馈线性化和反步设计的思想设计非线性预测控制器。该控制器在模型带有不确定性时更易使闭环系统稳定,且动态特性良好。以北海油田某区块为例进行的仿真研究结果验证了控制器是有效的。Applying of intelligent well, which is frontier technology used in oil production industry, transfers well controller from well surface to down hole. To resolve the difficulties of down hole control, which are arisen from the impossibility of acquiring the exact reservoir parameters and the strongly nonlinearity of fluid flow, a nonlinear model predictive controller for model with uncertainty was designed. Firstly, a control model with uncertainty was built. Then, a nonlinear model predictive controller was proposed by using feedback linearization method and backstepping design. By using the controller, not only the stability of closed loop system can be acquired more easily, but also the dynamic behavior is good even uncertainty exited in the model. The validity of the controller can be verified by simulation results of a reservoir located at North Sea Oilfield.
分 类 号:TP27[自动化与计算机技术—检测技术与自动化装置]
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