Control structure selection of increased-pressure extractive distillation process for DMC-MeOH azeotropic mixture

Producing dimethyl carbonate (DMC) as a green chemical with the desired purity is important in the industry. Although studies on the steady-state design of energy-efficient extractive distillation processes are important for the purification of DMC-methanol (DMC-MeOH) azeotropic mixtures, the dynamic controllability of these processes is also critical in the case of feed condition changes, and it should be investigated carefully. Results of the limited studies in the literature show that changing the operating pressures in extractive distillation processes might have different effects on the dynamic controllability of different systems. Thus, in this study, alternative control strategies are developed for a recently proposed increased-pressure extractive distillation process to separate DMC-MeOH mixture. All control structures are designed using inferential temperature controllers, which have a general acceptance in industrial applications. Effects of different ratio controllers are investigated by evaluating the dynamic responses of control structures for disturbances in feed flowrate and composition. Two metrics including integral absolute error and steady-state deviation of purities are used in the evaluation of alternatives. Results of dynamic simulations show that a control structure including reflux ratio controller is not a suitable strategy for this process. It is demonstrated that a control structure including reflux to feed ratio controller for both distillation columns is necessary for the robust and efficient control of a pressure-increased extractive distillation process. These efficient dynamic results support the economic advantage of increased-pressure extractive distillation process separating DMC-MeOH azeotropic mixtures.     

Integrating process and controller models for the design of self-optimizing control

The steady-state behavior of an existing plant depends on the independent input variables, process equipment and process controllers. This paper presents a method for formulating models that represent the effects of controllers when they are included within a steady-state process flowsheet. The method replaces the controller equations with the equivalent stationarity conditions representing the relationship between the controlled variables and the implemented manipulated variables at steady state. The method is demonstrated for the centralized multivariable Dynamic Matrix Control algorithm applied to two processes, binary distillation and gasoline blending. The integrated process and control system simulation is used to design controllers that improve the profitability of processes without extensive real-time calculations; this is sometimes termed self-optimizing control. For both processes, controllers were designed that yielded higher profit than standard control methods and that approached the highest possible profit achieved by frequent real-time optimization.     

ON THE DESIGN OF ROBUST CONTROL SYSTEMS FOR DISTILLATION COLUMNS

The distillation column dynamics is very nonlinear, especially at high purity. Multivariable control system designs, which are essentially linear, may not be able to perform well at different operating conditions. This paper looks at three different multivariable design techniques—decoupling control, optimal state feedback and pole assignment as applied to distillation column control. Robustness of these techniques are analyzed by looking at the performance of these controllers at different operating conditions. Some interesting results are obtained.     

蒸馏塔分散PID控制器整定研究

结合一种双输入双输出 (TITO)分散PID控制器的设计方法 ,并将其应用于乙醇—水的蒸馏分离过程控制中。该法根据相应的收敛性算法 ,通过一系列继电闭环实验辨识预期临界点 (DCP) ,利用T L整定公式获取分散PID控制器参数。通过仿真对比试验 ,表明所设计的控制系统具有满意的动态性能     

Temperature Inferential Control of Heat‐Integrated Distillation Column Based on Variable Sensitive Stage Temperature Set‐point

Heat‐integrated distillation is an improved distillation technique with remarkable energy‐saving potential. A control scheme with a variable sensitive stage temperature set‐point is proposed to solve the control problem of a heat‐integrated distillation column (HIDiC). An online estimator is designed to support the variation of the set‐point. The locations of the stage temperature measurements are carefully selected based on a combination strategy with three steps. First, the sensitive stages are selected. Then, the following stages are determined by a PCA‐based method. Finally, a maximum differentiation method provides the remaining measurement selections. According to the profile parameters estimated by the proposed estimator, the set‐point of the sensitive stage temperature is adjusted adaptively to reduce the influence of the disturbances. Two commonly‐used PID controllers, the sensitive temperature control and the temperature differential control, are developed as the comparative study. The simulation results show that the proposed control scheme has a distinct advantage in restraining different disturbances.     

Identification and Control of an Industrial Binary Distillation Column: A Case Study

The challenging problem of identification and control of an industrial binary distillation column is addressed in this paper. Process identification represents an alternative to modeling and is shown to be the appropriate procedure for predictive control design. The predictive controllers based on the identified model ensure stability and high performance for a wide operating range of the industrial distillation column.     

Sampled-data feedback control of a binary distillation column

The design of sampled-data controllers for a binary distillation column was studied for several types of controllers and for various control tray locations, sampling rates and disturbances. Minimal prototype control was superior to continuous PI control under some conditions but, as expected, was only satisfactory for a specified disturbance. dual “A” control scheme that compensates for both setpoint and load disturbances was developed. Two separate algorithms are implemented simultaneously, one receiving its input signal from the setpoint and the other from the measured variable. Dual control is superior to continuous control, particularly when both disturbances are encountered at the same time, and is superior to the “switching” method proposed by Mosler et al.     

Tracking the predefined optimal policies for multiple-fraction batch distillation by using adaptive control

Predefined optimal policies will be tracked with control systems to realize the optimum of multiple-fraction batch distillation. Adaptive control is proposed to carry out this task. Characteristics of batch distillation control are analyzed and a proper system is designed for controlling such processes. Besides tracking the optimal reflux ratio profile, the maximum vapor load will be maintained during the batch. In addition, a changing temperature profile of the condenser should be followed to reduce the operating energy with a possibly minimum subcooling. Recursive least square estimation (RLSE) with a variable forgetting factor is applied to the on-line identification of the plant to follow the changing dynamics of the process. Generalized predictive control (GPC) is used to track the predefined policies. The effectiveness of the control strategy is verified with a pilot batch column and the tracking performance is compared with that of PID controllers.     

Applying Model Predictive Control to Dividing Wall Columns

The technology of dividing wall columns can offer enormous energy savings compared to common distillation columns and configurations. The technology of model predictive control is also advantageous since such a controller minimizes the future deviation of the predicted controlled variable from the reference point. The practical application of model predictive controllers for dividing wall columns is still limited due to limited experience with high interactions among the process variables. The scope of this work is the development and analysis of a method for the design of model predictive controllers for dividing wall columns. An experimental investigation verifies the practicability of the applied approach. The methods generated are transferable to other applications. Thus, the industrial acceptance of model predictive controllers for dividing wall columns is enhanced.     

Modelling and control of a continuous distillation tower through fuzzy techniques

This paper presents a methodology for the design of a fuzzy controller applicable to continuous processes based on local fuzzy models and velocity linearizations. It has been applied to the implementation of a fuzzy controller for a continuous distillation tower. Continuous distillation towers can be subjected to variations in feed characteristics that cause loss of product quality or excessive energy consumption. Therefore, the use of a fuzzy controller is interesting to control process performance.A dynamic model for continuous distillation was implemented and used to obtain data to develop the fuzzy controller at different operating points. The fuzzy controller was built by integration of linear controllers obtained for each linearization of the system. Simulation of the model with controller was used to validate the controller effectiveness under different scenarios, including a study of the sensibility of some parameters to the control.The results showed that the fuzzy controller was able to keep the target output in the desired range for different inputs disturbances, changing smoothly from a predefined target output to another. The developed techniques are applicable to more complex distillation systems including more operating variables.     

TUNING METHOD FOR INTERACTIVE MULTILOOP IMC, PI AND PID CONTROLLERS

An efficient method to adjust a multiloop control system based on IMC, PI or PID controllers is presented. The first step of the new method consists in designing and adjusting the individual IMC controllers assuming a noninteractive condition and using information related to model uncertainties. In a second step, a single tuning parameter is used to adjust the multiloop interactive system in order to improve both stability and performance characteristics. The extension to multiloop PI and PID controllers is made through alternative parameterizations of IMC (Rivera el al., 1986).

Several simulation results obtained using transfer function representations of distillation systems from the literature show the convenience of the proposed technique by yielding good settings with a reasonable amount of engineering and computational effort.     

Dynamic Study of Distillation Column Operated with Tray Heat Source Combined with Reboiler

This work reports experimental tests using the distribution of energy in distillation by applying internal heat sources combined with a reboiler in order to reduce the transition time when the process is disturbed. In this way, a dynamic study was undertaken in a pilot column with ethanol and water, comparing the effects of a step disturbance in the reboiler and the same heat quantity in the intermediate tray of the column. The results showed that the use of the combined heat supply reduced the hydraulic delay in the distillation column and, consequently, the transition time. In this way, this study suggests that it is possible to use the heat distribution to control a distillation column using classical strategies and simple controllers, such as proportional-integral-derivatives (PID), and with this obtain faster responses.     

Evaluation of a two-temperature control structure for a two-reactant/two-product type of reactive distillation column

Several different control structures have been proposed for reactive distillation columns. The appropriate control structure depends on the flowsheet and on the type of reactions occurring in the column. If two reactants are involved and if it is desirable to operate the process without any excess of reactant, it is necessary to manage the fresh feed streams so that the stoichiometry is exactly balanced. A composition analyzer that measures an internal composition in the column is often required. However, if two products are produced, it is possible to avoid the use of an analyzer by using two temperatures in the column to adjust the two feed streams. This type of structure was proposed by Roat et al. [Roat, S., Downs. J., Vogel, E., Doss, J., 1986. Integration of rigorous dynamic modeling and control system synthesis for distillation columns. In: Chemical Process Control—CPC III. Elsevier, Amsterdam.] for the ideal reaction A+B↔C+D in one of the earliest papers dealing with reactive distillation control.The purpose of this paper is to explore the effectiveness of this two-temperature control structure for various column designs (number of reactive stages) to quantify the impact of design on controllability. We also discuss the issues of the selection of the trays whose temperatures are to be controlled and the tuning of the two interacting temperature controllers. Disturbances in production rate and fresh feed compositions are made to examine the rangeability of this control structure. Both an ideal reaction system and the methyl acetate system are studied. One of the main conclusions is that the locations of the temperature control trays should be made such that the two temperature controllers both have direct action (an increase in temperature increases feed), which requires negative openloop process gains for both loops.     

Dissipativity‐based distributed model predictive control with low rate communication

Distributed or networked model predictive control (MPC) can provide a computationally efficient approach that achieves high levels of performance for plantwide control, where the interactions between processes can be determined from the information exchanged among controllers. Distributed controllers may exchange information at a lower rate to reduce the communication burden. A dissipativity‐based analysis is developed to study the effects of low communication rates on plantwide control performance and stability. A distributed dissipativity‐based MPC design approach is also developed to guarantee the plantwide stability and minimum plantwide performance with low communication rates. These results are illustrated by a case study of a reactor‐distillation column network. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3288–3303, 2015     

Distributed Heat Supply for Distillation Control to Reduce Feed Composition Disturbance Effects

The introduction of heat in stages combined with a reboiler as a distillation control strategy is proposed aiming to reduce the transition time when a feed composition disturbance occurs. This is the most severe type of perturbation and results in long transition times which are economically undesirable. Experiments were carried out in a pilot distillation column with ethanol and water for testing two different control strategies: conventional, i.e., using both last stage and reboiler temperature controllers, and distributed, i.e., conventional strategy plus stage temperature controllers. The results with this operational approach indicated a significant reduction in the time required for the column to stabilize when compared with the conventional approach. The proposed strategy proved to be a viable alternative, enabling faster dynamics and smaller volumes to be processed outside the predefined quality parameters.     

System identification and PID controller tuning using band-pass filters

An online recursive system identification technique using band-pass filters has been developed to estimate the continuous-time frequency response of any process control system at a number of discrete frequencies. Tuning of PID controllers employs a gradient optimization technique, based on the estimated discrete frequency response of the process rather than a transfer function model of the process. The performances of the identification technique and controller tuning algorithm are demonstrated by a simulation and by experimental results on a distillation column composition control.     

About the possibility of a direct concentration control for distillation columns

The results of simulations of direct concentration control of a distillation column in industrial scale are presented. Both controlled variables, the two product concentrations, are determined by on-line gas chromatographs and are characterised by high dead times of about 30 min. For the resulting scanning control of the product concentrations corresponding decentralised PI controllers were developed and applied. The control of the product concentrations developed presents a conventional DV structure and was exemplarily tested for disturbances in feed flow and feed concentrations. The calculations carried out exhibit a good time behaviour of the whole system. On this occasion it can be stated that the control quality could be clearly improved if a steady-state decoupling by output transformation was employed. In this case the results achieved are totally comparable to those of internal model control (IMC), which was in use at the production plant for over two years.     

Energy‐efficient complex distillation sequences: Control properties

Four thermally coupled distillation systems were designed for the separation of five‐component mixtures (the light‐ends separation section of a crude distillation plant); their steady‐state design was obtained by starting from a conventional distillation sequence and then optimizing for minimum energy consumption. The thermally coupled distillation systems were compared to sequence based on conventional columns design. Comparison was based on controllability properties under open and closed loop operation, following the dynamic behaviour after common industrial operating disturbances. Simulation results were analyzed by the singular value decomposition technique and with the performance examination of elimination of feed disturbances using PI controllers. It was found that thermally coupled distillation systems are controllable and, sometimes, they exhibit dynamic responses that are easier to manage than in the case of conventional distillation sequences; this result is innovative in the study of this kind of systems.     

A control perspective on process intensification in dividing-wall columns

During the last decades, process intensification led to major developments also in separation technology. Particularly in distillation, dividing-wall column (DWC) is the next best thing as it allows significant energy savings combined with reduced investment costs. However, in spite of these clear advantages and the steady increase of DWC applications, the spreading of DWC at industrial scale is still limited to only a few companies. One of the major reasons for this status quo is the insufficient insight with regard to the operation and control of a DWC - this lack of knowledge making most chemical companies reticent to large-scale implementations. This study gives an overview of the available control strategies for DWC, varying from the classic three-point control structure and PID controllers in a multi-loop framework to model predictive control (MPC) and other advanced control strategies (LQG, LSDP, H_∞ and μ-synthesis). The previous studies prove that the DWC is not difficult to control providing that an appropriate control structure is selected. The available results show that MIMO controllers perform better than multi-loop PID controllers. However, among the decentralized multivariable PI structured controllers, LSV and DSV are the best control structures being able to handle persistent disturbances in reasonably short times. All things considered, this study clearly concludes that the DWC controllability is only perceived as a problem, but in fact there are no real solid grounds for concern.     

Enhancing Controller Performance via Dynamic Data Reconciliation

Measured values of process variables are subject to measurement noise. The presence of measurement noise can result in detuned controllers in order to prevent excessive adjustments of manipulated variables. Digital filters, such as exponentially weighted moving average (EWMA) and moving average (MA) filters, are commonly used to attenuate measurement noise before controllers. In this article, we present another approach, a dynamic data reconciliation (DDR) filter. This filter employs discrete dynamic models that can be phenomenological or empirical, as constraints in reconciling noisy measurements. Simulation results for a storage tank and a distillation column under PI control demonstrate that the DDR filter can significantly reduce propagation of measurement noise inside control loops. It has better performance than the EWMA and MA filters, so that the overall performance of the control system is enhanced.