Direct and Indirect Gradient Control for Static Optimisation

Static “self-optimising” control is an important concept, which provides a link between static optimisation and control. According to the concept, a dynamic control system could be configured in such a way that when a set of certain variables are maintained at their setpoints, the overall process operation is automatically optimal or near optimal at steady-state in the presence of disturbances. A novel approach using constrained gradient control to achieve “self-optimisation” has been proposed by Cao. However, for most process plants, the information required to get the gradient measure may not be available in real-time. In such cases, controlled variable selection has to be carried out based on measurable candidates. In this work, the idea of direct gradient control has been extended to controlled variable selection based on gradient sensitivity analysis (indirect gradient control). New criteria, which indicate the sensitivity of the gradient function to disturbances and implementation errors, have been derived for selection. The particular case study shows that the controlled variables selected by gradient sensitivity measures are able to achieve near optimal performance.

Novel eco-efficient reactive distillation process for dimethyl carbonate production by indirect alcoholysis of urea

Dimethyl carbonate is an eco-friendly essential chemical that can be sustainably produced from CO_(2),which is available from carbon capture activities or can even be captured from the air.The rapid increase in dimethyl carbonate demand is driven by the fast growth of polycarbonates,solvent,pharmaceutical,and lithium-ion battery industries.Dimethyl carbonate can be produced from CO_(2)through various chemical pathways,but the most convenient route reported is the indirect alcoholysis of urea.Previous research used techniques such as heat integration and reactive distillation to reduce the energy use and costs,but the use of an excess of methanol in the trans-esterification step led to an energy intensive extractive distillation required to break the dimethyl carbonate-methanol azeotrope.This work shows that the production of dimethyl carbonate by indirect alcoholysis of urea can be improved by using an excess of propylene carbonate(instead of an excess of methanol),a neat feat that we showed it requires only 2.64 kW·h·kg^(-1) dimethyl carbonate in a reaction-separation-recycle process,and a reactive distillation column that effectively replaces two conventional distillation columns and the reactor for dimethyl carbonate synthesis.Therefore,less equipment is required,the methanol-dimethyl carbonate azeotrope does not need to be recycled,and the overall savings are higher.Moreover,we propose the use of a reactive distillation column in a heat integrated process to obtain high purity dimethyl carbonate(>99.8 wt-%).The energy requirement is reduced by heat integration to just 1.25 kW·h·kg^(-1) dimethyl carbonate,which is about 52%lower than the reaction-separation-recycle process.To benefit from the energy savings,the dynamics and control of the process are provided for10%changes in the nominal rate of 32 ktpy dimethyl carbonate,and for uncertainties in reaction kinetics.

Distributed Control of Chemical Process Networks

In this paper,we present a review of the current literature on distributed(or partially decentralized) control of chemical process networks.In particular,we focus on recent developments in distributed model predictive control,in the context of the specific challenges faced in the control of chemical process networks.The paper is concluded with some open problems and some possible future research directions in the area.