Moving horizon approach of integrating scheduling and control for sequential batch processes

Abstract

Online integration of scheduling and control is crucial to cope with process uncertainties. We propose a new online integrated method for sequential batch processes, where the integrated problem is solved to determine controller references rather than process inputs. Under a two-level feedback loop structure, the integrated problem is solved in a frequency lower than that of the control loops. To achieve the goal of computational efficiency and rescheduling stability, a moving horizon approach is developed. A reduced integrated problem in a resolving horizon is formulated, which can be solved efficiently online. Solving the reduced problem only changes a small part of the initial solution, guaranteeing rescheduling stability. The integrated method is demonstrated in a simulated case study. Under uncertainties of the control system disruption and the processing unit breakdown, the integrated method prevents a large loss in the production profit compared with the simple shifted rescheduling solution.

A novel adaptive surrogate modeling‐based algorithm for simultaneous optimization of sequential batch process scheduling and dynamic operations

“…The objective of inner level problems is to minimize the total processing cost over all stages at the given processing time. The optimal objective value in the inner level problem is a function of processing time, which is referred to as the optimal-value function (18) and also appears in the outer level problem as Eq. 17.…”

“…The objective is to maximize the total profit over the entire production horizon. [15][16][17][18] Previous work has been reported in the literature on the integrated batch scheduling problem for complex batch distillation and batch reactor/distillation processes. 19,20 In addition, mathematical programming approach and efficient solution methodology have been proposed to determine the design parameters and operating policy for batch distillation processes simultaneously.…”

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

“…Chu and You use a moving future horizon for online recalculation of integrated scheduling and control for batch processes in the presence of disturbances such as unit breakdowns and system disruptions and a dual feedback structure to reduce the frequency of integrated problem solution [12]. Pattison et al investigate using a scale-bridging model (SBM) in a closed-loop moving horizon implementation of integrated scheduling and control for an industrial air separation unit (ASU), demonstrating effective response to planned maintenance, unplanned maintenance, and random failure scenarios [14].…”

“…Additionally, dynamic optimization control problems are not required to be solved only once, as in an iteration of advanced online control, but for each grade transition during a production schedule. The integrated scheduling and control (ISC) problem has been shown to be computationally difficult, and much research has been invested in decomposition and reduction of computational burden for the problem [8][9][10][11][12].…”

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

“…They propose using multi-parametric model predictive control for online batch scheduling and control [48], fast model predictive control coupled with reduced order (piece-wise affine) models in scheduling and control for continuous processes [49], and decomposition into separate problems for continuous processes [50]. Chu and You demonstrate the economic benefit of closed-loop moving horizon scheduling with consideration of process dynamics in batch scheduling [29]. Chu and You also investigate the reduction of computational burden to enable online closed-loop ISC for batch and continuous processes.…”