Amiya K. Jana

Dynamic simulation and nonlinear control of a rigorous batch reactive distillation.

This work deals with the dynamics and control of a high-purity batch distillation column with chemical reaction. A heterogeneous esterification reaction between the acetic acid and butanol takes place to produce butyl acetate. The process model is formulated considering variable liquid holdup, UNIQUAC model for thermodynamic property predictions, nonlinear Francis weir formula for tray hydraulics, pseudohomogeneous model to represent the reaction kinetics and rigorous energy balance. A structured and simple iterative approach is devised to compute the vapor flows with the fast convergence, under the rigorous energy balance. The representative column is treated with a distillate policy based on which, the lightest product, water is removed as distillate at the starting of production phase. As a consequence, the column gets progressively richer with the main product, butyl acetate. In addition, almost complete conversion of the limiting reactant is achieved. In order to maintain the product purity at the top, a nonlinear generic model controller (GMC) in two different forms has been proposed. Finally, a comparative closed-loop performance is addressed. It is shown that the control scheme, along with the effective distillate strategy, leads to almost complete conversion of ingredients and high-purity products.

Neuro-estimator based GMC control of a batch reactive distillation

In this paper, an artificial neural network (ANN)-based nonlinear control algorithm is proposed for a simulated batch reactive distillation (RD) column. In the homogeneously catalyzed reactive process, an esterification reaction takes place for the production of ethyl acetate. The fundamental model has been derived incorporating the reaction term in the model structure of the nonreactive distillation process. The process operation is simulated at the startup phase under total reflux conditions. The open-loop process dynamics is also addressed running the batch process at the production phase under partial reflux conditions. In this study, a neuro-estimator based generic model controller (GMC), which consists of an ANN-based state predictor and the GMC law, has been synthesized. Finally, this proposed control law has been tested on the representative batch reactive distillation comparing with a gain-scheduled proportional integral (GSPI) controller and with its ideal performance (ideal GMC).

Differential Geometry-Based Adaptive Nonlinear Control Law: Application to an Industrial Refinery Process

In this contribution, an extended generic model control (EGMC) law is proposed based on differential geometry theory. This multivariable nonlinear control system requires the knowledge of the internal state of the process. To cope with this, an adaptive control scheme is formulated here. This adaptive nonlinear control law combines the EGMC with the Luenberger-type nonlinear state estimator (LNSE). Deriving the control law and the state estimator, the stability properties of the EGMC, LNSE and the combined EGMC-LNSE structure are developed. The application and performance of the proposed adaptive EGMC-LNSE control law are finally illustrated by a simulated industrial refinery process (i.e., debutanizer). The representative column has 169 state variables, and it was operated in the province of Alberta, Canada. It is surprising to note that the LNSE scheme aims to estimate a few states that are solely required for the controller based on only two component balance equations. As a consequence, there exists a significant structural discrepancy and despite it, the proposed nonlinear controller shows its superiority over the multivariable dynamic matrix controller.

A Hybrid FLC-EKF Scheme for Temperature Control of a Refinery Debutanizer Column

A nonlinear feedback linearizing control (FLC) strategy is proposed within the differential geometric framework for temperature control of a refinery debutanizer column. The distillation model is verified by real data. The FLC control algorithm usually consists of a transformer, a state estimator and an external linear controller. Here, two state estimators, namely extended Kalman filter (EKF) and short-cut model-based open-loop estimator (SMBOLE), have been developed to device the hybrid FLC-EKF and FLC-SMBOLE control systems, respectively. In order to avoid estimator design complexity as well as computational burden, an ideal binary distillation model [light key (LK)/heavy key (HK)] has been used as an EKF predictor and open-loop estimator (OLE). In this article, a comparative study has been conducted between the FLC-EKF, FLC-SMBOLE and a classical dual-loop proportional integral derivative (PID) control structure. Simulation results show that despite the significant process/model mismatch, the proposed FLC controllers perform better than the PID control scheme.

Nonlinear State Estimation and Generic Model Control of a Continuous Stirred Tank Reactor

The goal of this paper is to develop a nonlinear observer-based control strategy for a jacketed continuous stirred tank reactor (CSTR). The nonlinear adaptive state estimator/observer (ASE/ASO) is designed based on a model structure that mainly consists of an energy balance equation. In this observation approach, reactor concentration is considered as an imprecisely known extra state (augmented state) with no dynamics. Despite significant process/model discrepancy, the proposed state observer estimated adequately the states of the simulated reactor. Mainly due to the design simplicity, negligible computational effort and fast convergence, the observer is recommended for online implementation. The generic model controller (GMC) has also been synthesized for the example reactor. The nonlinear GMC scheme receives the required information about the reactor concentration from the ASE for calculating the controller responses. Simulation experiments have been carried out to investigate the superior performance provided by the proposed GMC-ASE algorithm compared to the conventional proportional integral (PI) controller.

Nonlinear model-based control algorithm for a distillation column using software sensor

This paper presents the design of model-based globally linearizing control (GLC) structure for a distillation process within the differential geometric framework. The model of a nonideal binary distillation column, whose characteristics were highly nonlinear and strongly interactive, is used as a real process. The classical GLC law is comprised of a transformer (input-output linearizing state feedback), a nonlinear state observer, and an external PI controller. The tray temperature based short-cut observer (TTBSCO) has been used as a state estimator within the control structure, in which all tray temperatures were considered to be measured. Accordingly, the liquid phase composition of each tray was calculated online using the derived temperature-composition correlation. In the simulation experiment, the proposed GLC coupled with TTBSCO (GLC-TTBSCO) outperformed a conventional PI controller based on servo performances with and without measurement noise as well as on regulatory behaviors. In the subsequent part, the GLC law has been synthesized in conjunction with tray temperature based reduced-order observer (GLC-TTBROO) where the distillate and bottom compositions of the distillation process have been inferred from top and bottom product temperatures respectively, which were measured online. Finally, the comparative performance of the GLC-TTBSCO and the GLC-TTBROO has been addressed under parametric uncertainty and the GLC-TTBSCO algorithm provided slightly better performance than the GLC-TTBROO. The resulting control laws are rather general and can be easily adopted for other binary distillation columns.

Analysis and control of a partially heat integrated refinery debutanizer

In this contribution, the internal heat integration concept has been applied on a commercial refinery debutanizer column for the separation of an eight-component hydrocarbon mixture. Here, the thermodynamic feasibility of this process has been identified. Then, an economically interesting partially heat integrated debutanizer column (HIDBC) configuration is explored. A sensitivity test has been conducted to select the compression ratio required to meet the product specification. This study deals with the parametric analysis to investigate the effect of important parameters on product purity and energy consumption. An economic comparison between the conventional debutanizer and the proposed thermally coupled debutanizer scheme is also performed. This paper proposes a control algorithm that considers the control of most sensitive tray temperatures. The singular-value decomposition (SVD) method is used for selecting the sensitive trays. Finally, the closed-loop control performance of the HIDBC has been examined. Due to the internal energy integration, better performance is achieved with up to 44% energy saving and more than 14% saving in total annual cost.

Nonlinear state estimation and control of a refinery debutanizer column

Abstract This article concerns the issue of designing a nonlinear model-based controller for a refinery debutanizer column. First, a nonlinear adaptive state estimator/observer (ASE/ASO) was developed based on a simple observer model structure that mainly consists of only two component balance equations around the condenser-cum-reflux drum and the reboiler-cum-column base. In this observation approach, vapor flow rate of component nC5 (heavy key) leaving top tray, liquid flow rate of component nC4 (light key) leaving bottom tray and distribution coefficient of component n C4 in the reboiler were considered as extra states with no dynamics. Despite process/model mismatch, the proposed state observer estimated the required states of a simulated debutanizer column precisely. Mainly due to the design simplicity, negligible computational effort and fast convergence, the observer is recommended for online implementation. In the subsequent part, the globally linearizing control (GLC) structure, which was consisted of a nonlinear transformer (input–output linearizing state feedback), a linear external controller and an adaptive state observer, has been synthesized. The hybrid GLC–ASO control algorithm provided promising performance compared to the proportional integral (PI) controller that has been thoroughly investigated on the complex refinery debutanizer column.

Simulation and Control of a Commercial Double Effect Evaporator: Tomato Juice

This work aims to present a detailed study on a commercial double-effect tomato paste evaporation system. The modeling equations formulated for process simulation belong to backward feeding arrangement. Open-loop process dynamics has been studied by rigorous simulation of the model structure. In the next, three multi-loop control schemes, namely conventional proportional integral (PI), gain-scheduled PI (GSPI) and nonlinear PI (NLPI), have been synthesized for the sample process. Finally, several simulation experiments have been conducted to investigate the comparative closed-loop performance based on set point tracking and disturbance rejection.

Process Simulation and Design of Reactive Distillation Column

This paper presents a systematic study on the homogeneously catalyzed reactive distillation (RD) process operated in both batch and continuous mode for the synthesis of ethyl acetate. In the first part, the fundamental model has been developed incorporating the reaction term within the model structure of the nonreactive distillation process. In case of batch rectifier, the process operation is simulated at the startup phase under total reflux condition for reaching the steady state. The open-loop process dynamics are also examined running the batch process at production phase under partial reflux condition.The concerned batch rectifier has the ability to provide high purity product. On the other hand, the continuous RD column exampled at the beginning of the second part produces relatively low quality product. In the present study, an attempt has been made to configure a feasible continuous column with improved product quality. In order to propose a RD setup, several simulation experiments have been performed for sensitivity analysis. An interesting phenomenon, the input multiplicity, is observed for both the batch as well as continuous column.