Predictive PDF control in shaping of molecular weight distribution based on a new modeling algorithm. (June 2015)

• Record Type: Journal Article
• Authors: Zhang, Jinfang; Yue, Hong; Zhou, Jinglin
• Is Part Of: Journal of process control. Volume 30(2015:Jun.)
• Page Start: 80
• Page End: 89
• Publication Date: 2015-06
• Subjects: Probability density function (PDF) -- B-spline approximation -- Parameter estimation -- Model predictive control (MPC) -- Molecular weight distribution (MWD); Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2014.12.009
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract : Highlights: Integrated the idea of model predictive control to output PDF control. Proposed a new RSR B-spline modeling algorithm to establish dynamic PDF model based on data of control input and output PDF. The stability of the unique modeling is analyzed with an output feedback control structure. Developed predictive control algorithms for output PDF control systems. Developed a simulation system for a lab-scaled MWD control process, and applied the proposed new modeling method and predictive PDF control strategies to this system to assess the modeling efficiency and the merits of predictive PDF control. Abstract: The aims of this work are to develop an efficient modeling method for establishing dynamic output probability density function (PDF) models using measurement data and to investigate predictive control strategies for controlling the full shape of output PDF rather than the key moments. Using the rational square-root (RSR) B-spline approximation, a new modeling algorithm is proposed in which the actual weights are used instead of the pseudo weights in the weights dynamic model. This replacement can reduce computational load effectively in data-based modeling of a high-dimensional output PDF model. The use of the actual weights in modeling and control has been verified by stability analysis. A predictive PDF model is then constructed, based on which predictive control algorithms are established with the purpose to drive the output PDF towards the desired target PDF over the control process. An analytical solution is obtained for the non-constrained predictive PDF control. For the constrained predictive control, the optimal solution is achieved via solving a constrained nonlinear optimization problem. The integrated method of data-based modeling and predictive PDF control is applied to closed-loop control of molecular weight distribution (MWD) in an exemplar styrene polymerization process, through which the modeling efficiency and the merits of predictive control over standard PDF control are demonstrated and discussed.