【摘要】 In this paper,a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process.In the upper layer,the variant time scale based control vector parametric methods(VTS-CVP) was used for dynamic optimization of transition reference trajectory,while nonlinear model predictive controller(NMPC) based on closed-loop subspace and piece-wise linear(SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances.Besides,mechanism about trajectory deviation detection and optimal trajectory updating online were introduced to ensure a smooth transition for the entire process.The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanism mathematical model.更多还原

【Abstract】 In this paper,a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process.In the upper layer,the variant time scale based control vector parametric methods(VTS-CVP) was used for dynamic optimization of transition reference trajectory,while nonlinear model predictive controller(NMPC) based on closed-loop subspace and piece-wise linear(SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances.Besides,mechanism about trajectory deviation detection and optimal trajectory updating online were introduced to ensure a smooth transition for the entire process.The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanism mathematical model.更多还原