Control structure selection

Evaluation of R/Fand RR Structures. The first thing to do is to explore the effect of feed composition on the required changes in reflux-to-feed and reflux ratio whde holding the two products at their specified values. The specifications are 99.5 mol% water purity in the distillate and 12mol% water impurity in the bottoms. 

These results clearly display a strong preference for a constant R/F ratio structure. The reflux-to-feed ratio only changes about 10% over the entire range of feed compositions, while the reflux ratio changes over 60%. 

But the reflux ratio is quite high (RR = 9.16 at design). The reflux-drum level should be controlled by reflux flow rate when the reflux ratio is this large, which would preclude the use of the reflux-to-feed control stracture. In the following section, a control structure that permits the use of the R/F scheme is developed. 

It should be emphasized that the analysis discussed in this section considers only steady-state effects. Dynamics are not considered. However, just because a control structure looks 

Control Structure Holding Reflux-Drum Level with Reboiler Heat Input. The 

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P. A. Wisnewski and F. J. Doyle, Control structure selection and model predictive control of the Weyerhaeuser digester problem, J. Process Control, 8, 487—495 (1998). 

Later on, the complexities introduced by process integration were fully acknowledged by researchers in the field, and motivated a series of studies on the effect of the material recycle streams on the design, controllability, and control structure selection for specific reaction/separation processes. 

In the 1960s and 1970s, the relative gain array (RGA) [19] was the only systematic tool available for control structure selection. Its simplicity, practical success, and lack of theoretical basis were disturbing to many academics. Since then, the RGA has been largely vindicated its range of applicability has been defined, its limitations are well understood, and its... 

A number of research issues in the areas of robust control, model predictive control, and control structure selection were mentioned previously. Unfortunately, even if all these problems were solved, a practical problem like the Shell Control Problem [23] could still not be tackled in a systematic fashion. All the research topics discussed so far in this paper are re-... 

In this book, we focus primarily on control structure selection. Interactions between design and control are illustrated by examples, and the effects of design parameters on control are discussed. However, we do not present a synthesis procedure for process design that is capable of generating the most conriollable flowsheet for a given chemistry. This is still very much an open area for further research. 

Control system design consists of two steps control stmcture selection includes the choice of suitable manipulated and measured variables as well as their pairing design and parameterization of some control algorithm defines the computation of the required values of the manipulated variables from the measurements and given set-points. Let us first focus on the control structure selection problem. 

In the previous case study, the focus was on control structure selection. As control algorithms standard linear Pl-controllers were used. In a second case study, the focus is on control algorithms. For that purpose we compare different control algorithms for a fixed control stmcture. The process to be considered is an industrial benchmark problem, which was treated in joint research with Bayer AG [21, 33]. The process and its open loop dynamic behavior is illustrated in Fig. 10.29. Components B and C are the reactants. They react in two consecutive equilibrium reactions to products A and E. The main product E is obtained in the bottoms of the column and the other product A in the distillate. 

The optimal control structure altvays depends on the specific type of process considered. Further research is required to develop more general guidelines for control structure selection of RD processes depending on the dominating process characteristics. 

STEADY-STATE CALCULATIONS FOR CONTROL STRUCTURE SELECTION... 

There are four remaining manipulated variables (distillate flow rate, bottoms flow rate, reboiler duty, and feed flow rate) to control these four controlled variables. The issue of pairing which manipulated variable with which controlled variable is called control structure selection. A variety of different types of control structures will be discussed in this and subsequent chapters. 

So the basic conventional control structure selected has reflux-to-feed ratio. This is implemented in Aspen Dynamics using a multiplier block (R/F) with one input being the molar flow rate of feed and the other input the specified reflux-to-feed molar ratio. Since Aspen Dynamics has the rather odd limitation of only being able to directly specify the mass flow rate of the reflux, a flow controller must be installed whose process variable signal is the reflux molar flow rate, and whose output signal is the reflux mass flow rate. This flow controller is put onto cascade with its set point signal coming from the R/F multiplier. 

CONVENTIONAL CONTROL STRUCTURE SELECTION 449 50% Feed increase TC with and w/o QR/F ratio... 

The steady-state and dynamic behavior in RD are addressed in this chapter. Fundamental understanding of multiplicity in a reactive flash is provided. Moreover, the domain knowledge is extended by dynamic analysis, whose tasks include model development, control structure selection, controller tuning and simulation of closed loop dynamics. The output of this section serves as reference case to be compared with that of the life-span inspired design methodology (c/. section 1.4). The material presented in this chapter answers partially Question 6. 

We have derived a new method for selecting controlled variables as linear combination of the available measurements, that from a linear point of view have perfect self-optimizing properties if we neglect implementation error. The idea is to calculate the optimal sensitivity function (Ayopt = FAd) and select controlled variables as linear combination of the measurements c = Hy, such that HF = 0. The method has been illustrated on a gas-lift allocation example. The example illustrate that in a constant set-point control structure, selecting the right controlled variables are of major importance. 

Control Structure Selection for Unstable Processes Using Hankel Singular Value... 

Control Structure Selection for open loop unstable processes is the main theme of this paper. Hankel singular value has been used as a controllability measure for input-output selection. This method ensures feedback stability of the process with minimal control effort as well as it provides a quantitative justification for the controllability. Simulation results with Tennesse-Eastman test-bed problem justify the proposed theory. 

One of the most important issues in Control Structure Selection is choosing appropriate screening criteria, viz. controllability measure, for input and output combinations. I/O selection is performed based on a plant model and a proposed set of candidate actuators and sensors. Reasons for not using all the available devices could be the reduction of control system complexity. 

Because of the increasing trend toward the production of low-volume/high-cost materials batch and semibatch processes become more and more important. In today s competitive markets, this implies the need for consistent high quality and improved performance. Over the last few years there has been growing interest in techniques for the determination of optimal operation policies for batch processes. Dynamic simulation has become a widely used tool in the analysis, optimisation, control structure selection and controller design. Some of the most recent work has been concerned with the mathematical optimisation of batch process performance (Li, 1998, Li et al., 1998). 

Engell and co-workers in Chapter C4 deal with the control structure selection based on input/output controllability measures. The limitations imposed by non-minimum phase characteristics on the attainable closed-loop performance are considered in the evaluation of the candidate set of control structure configurations. The optimisation of the attainable performance over the set of all linear stabilizing controllers can refine the controller structure with input constraints and coupling properties directly accounted for. 

S( — 1 if all the feed enters tray k, and is zero otherwise, and = 1 if the reflux enters tray k, and is zero otherwise. Additionally, a set of control binary variables 6f are introduced that are associated with each MV-CV pairing and are unity when the pairing exists and zero otherwise. The modelling of the control structure selection is carried our similarly to Narraway and Perkins [15]. These features lead to a mixed-integer dynamic distillation model. The principal differential-algebraic equations (DAEs) for the trays are given below. A full list of nomenclature, values of the parameters, details of the DAEs for the reboiler, condenser, reflux drum and control scheme, cost correlations for the objective function and inequality path constraints, can be found in Bansal et al, [7]. 

Regulatory control structure selection using linear economics and linear output feedback controllers... 

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