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Optimal Grade Transitions in a Gas-phase Polymerization Fluidized Bed Reactor

机译:气相聚合流化床反应器中的最佳等级转变

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Industrial polymerization plants experience frequent changes of products, driven by end-use properties to meet various market requirements. Good transition policies are essential to save time and materials. In this study, the gas-phase catalytic polymerization is modeled in a fluidized bed reactor by a single-phase model and dynamic optimization is implemented to determine optimal operating sequences for grade changes. Two optimization formulations, a single-stage and a multi-stage formulation, are introduced and compared. The superiority of the multi-stage formulation is concluded owing to better control at each stage during the transition and a further reduction of off-grade time. Subsequently, an on-line optimal control framework is established by incorporating a shrinking horizon nonlinear model predictive control with an expanding horizon weighted least-squares estimator for process states and unknown parameters. The results of a case study indicate the designed framework is able to overcome certain levels of uncertainty, while reducing the transition time.
机译:工业聚合厂经验经常改变产品,由最终用途的特性驱动,以满足各种市场要求。良好的过渡策略对于节省时间和材料至关重要。在该研究中,通过单相模型在流化床反应器中建模气相催化聚合,并实现动态优化以确定级变化的最佳操作序列。引入并比较了两种优化制剂,单级和多级配方。由于在过渡期间的每个阶段更好地控制,结论了多阶段制剂的优越性,并且进一步减少了离方级时间。随后,通过将收缩的地平线非线性模型预测控制结合到处理状态和未知参数的扩张地平线加权最小二乘估计器来建立一条在线最佳控制框架。案例研究的结果表明,设计的框架能够克服某些水平的不确定性,同时降低过渡时间。

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