Model Learning Predictive Control for Batch Processes: A Reactive Batch Distillation Column Case Study

Control strategies for reactive batch distillation

A batch reactor may be combined directly with a distillation column by distilling off the light component product in order to increase the reactor temperature or to improve the product yield of an equilibrium reaction. The same amount of the light product should be removed as the amount being formed by the reaction at any time. A linearized model has been developed which describes the process b...

2d Model Predictive Iterative Learning Control Schemes for Batch Processes

Iterative learning control (ILC) system is modelled and treated as a 2D system in this paper. Based on single-batch and multi-batch cost functions, 2D model predictive iterative learning control (2D-MPILC) schemes are developed in the framework of model predictive control (MPC) for the 2D system. Structure analysis shows that the resulted 2D-MPILC laws are causal and they implicitly combine a t...

Iterative learning model predictive control for multi-phase batch processes

Multi-phase batch process is common in industry, such as injection molding process, fermentation and sequencing batch reactor; however, it is still an open problem to control and analyze this kind of processes. Motivated by injection molding processes, the multi-phase batch process in each cycle is formulated as a switched system with internally forced switching instant. Controlling multi-phase...

Multicomponent batch distillation column design

Model Predictive Inferential Control of a Distillation Column

Typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. The distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. In this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive cont...