基于高斯模型的聚乙烯过程设计与控制集成优化

聚乙烯反应过程中物流-能流剧烈交叠、反应-传递相互耦合，使得过程具有强非线性以及多重稳态。传统的顺序设计方法不能保证系统有足够的控制自由度，当存在扰动和过程参数不确定性时，仅依靠设计控制器很难提高产品质量。提出一种聚乙烯工艺稳态设计与运行控制的集成优化方案，创造性地引入Kriging高斯模型同时预测模型动态和模型不确定性。另一个重要的贡献是在聚乙烯工艺设计阶段，设计性能指标，定量描述过程稳态设计对闭环动态的影响。所提出的方法已经通过对气相聚乙烯工艺设计和运行控制的集成优化进行了验证，并在参数不确定性和扰动存在情况下仿真证实了集成优化设计方案的高效性。

Simultaneous design and control of polyethylene process based on uncertainty Kriging model

Ethylene polymerization process has strong nonlinearity and multiple metastable states, driven by interaction between mass and energy transfer as well as compounded effect of polymerization and transport. Traditional sequential method of process design and control optimization in polymerization process is not capable of providing sufficient control freedom, which high quality products are difficult to manufacture by relying solely on design controller because of disturbance and uncertainty of process parameters. A new approach was proposed to integrate steady state design and control optimization for stable production of high performance polyethylene. The surrogate model (Kriging model) was introduced to simultaneously predict model dynamics and uncertainty. Model uncertainty was feasible space region of uncertain parameters bounded by coefficient confidence. A design performance index was defined to quantitatively interpret impact of steady state design on closed-loop dynamic behavior at process design stage. Closed-loop operating variability was quantified by model predictive controller that was to ensure process operate close to constraints and cost function of MPC that was to penalize deviations of predicted control outputs from reference operating point. The proposed method has been illustrated with integrated optimization of process design and operation control in gas-phase ethylene polymerization and method effectiveness is verified by process simulation under parameter uncertainty and disturbance.