Ratio and Cascade Control

After several cycles, the simulation is paused and the Finish test button on the bottom of the Tune window is clicked. The ultimate gain and ultimate period are displayed. For a 5 min deadtime, they arc Ku =2.9 and Py= 2 mins. For a 2 min deadtime, they are Ky = 4.3 and Pu = 5.4 min. 

Advanced control stmetores can be easily implemented in Aspen Dynamics. In this section we illustrate two of the more important methods. A simple distillation column is used to illustrate the installation of ratio elements (multipliers) and the use of cascade control. 

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These results illustrate the improvement in dynamic and steady-state performance that is achievable with conventional PI control structures through the use of ratio and cascade control schemes. Of course, on-line composition measurements are required for dualcomposition control. 

Advanced control is intended to provide improved performance over traditional single-loop control. It includes such techniques as multivariable, cascade, feedforward (including ratio), and inferential control. As noted already, overrides (Chapter 16) can be particularly helpful in dealing with variable constraints. 

Hint you will need to use the spreadsheet operation and cascade controllers. Using the ratios from Table W8.2 for direct control is not feasible. The correct approach for the control structure is outlined in Ryskamp [1 ]. 

There are many advanced strategies in classical control systems. Only a limited selection of examples is presented in this chapter. We start with cascade control, which is a simple introduction to a multiloop, but essentially SISO, system. We continue with feedforward and ratio control. The idea behind ratio control is simple, and it applies quite well to the furnace problem that we use as an illustration. Finally, we address a multiple-input multiple-output system using a simple blending problem as illustration, and use the problem to look into issues of interaction and decoupling. These techniques build on what we have learned in classical control theories. 

Apply classical controller analysis to cascade control, feedforward control, feedforward-feedback control, ratio control, and the Smith predictor for time delay compensation. 

Cascade control, along with ratio control, is used to control the temperature. The cold-water line is to have an air-to-close control valve. In case of failure in the air supply, the valve would open fully and a runaway reaction would be prevented. The hot-water line will have an air-to-open valve for similar reasons. After the two streams are mixed, the temperature will be measured. If it is above the desired temperature, the amount of air supplied to the valves will be reduced. This will increase the cold-water flow rate, and decrease the hot-water throughput. The result will be a reduction in the inlet water temperature. The desired temperature will be determined from a measurement of the reactor temperature. A deviation from the desired temperature will cause the set point of the second controller to be changed. This will result in a change of the inlet water temperature. 

Greg Shinskey (1988), over the course of a long and productive career at Foxboro, has proposed a number of advanced control" structures that permit improvements in dynamic performance. These schemes are not only effective, but they are simple to implement in basic control instrumentation. Liberal use should be made of ratio control, cascade control, override control, and valve-position (optimizing) control. These strategies are covered in most basic process control textbooks. 

Part V (Chapters 19 through 22) deals with the description, analysis, and design of more complex control systems, with one controlled output. In particular, Chapter 19 introduces the concept of feedback compensation with Smith s predictor, to cope with systems possessing large dead times or inverse response. Chapter 20 describes and analyzes a variety of multiloop control systems (with one controlled output) often encountered in chemical processes, such as cascade, selective, and split-range. Chapter 21 is devoted exclusively to the analysis and design of feedforward and ratio control systems, while Chapter 22 makes a rather descriptive presentation of adaptive and inferential control schemes why they are needed and how they can be used. 

Although feedback control is the type encountered most commonly in chemical processes, it is not the only one. There exist situations where feedback control action is insufficient to produce the desired response of a given process. In such cases other control configurations are used, such as feedforward, ratio, multivariable, cascade, override, split range, and adaptive control. 

To illustrate the cascade control approach, consider the control of the temperature of a jacketed crystallizer by manipulating the ratio of the flows to the crystallizer jacket from a heating stream and a cooling stream. The crystallizer temperature can be influenced by disturbances in the temperature of the heating and cooling streams and the heat transfer to the surroundings. Obviously, the crystallizer temperature could be measured and used in a feedback control scheme as shown in Figure 9.9 however, the manifestation of the disturbances would be slow, and the corrective action taken by the controller would be delayed. 

Another concept called shared digital control emerged. Simply, a microprocessor controller is used to control more than one loop. Using relatively cheap digital circuits, current microprocessor controllers can provide advanced functions such as cascade control, ratio control, feed-forward control, and other functions. 

However, over the years a number of slightly more complex structures have been developed that can, in some cases, significantly improve the performance of a control system. These structures include ratio control, cascade control, and override control. 

Fig. 2.8-17 Control strategies, a) Cascade control for the example level controls quantity , b) Ratio control for the example quantity of B controls quantity in a constant ratio , c) Split-range control for the example of temperature controls cold water In the range of 0.2—0.6 bar, and hot water in the range of 0.6—1.0 bar .

Even in the ab en(pe of preferential sputtering, i.e, SA=Sg, it is not necessarily the case that the concentration ratio of A and B is uniform with depth under steady state ion bombardment. The subsurface layer can have a different concentration ratio from the bulk or the top surface even if the latter two are identical. This can occur because of the subsurface effects of ion bombardment discussed below, which can produce an altered subsurface composition. As a result, there are two altered layers possible the top surface layer where composition at steady state is completely controlled by RgA and the subsurface layer where composition is controlled by segregation, radiation induced diffusion, radiation induced segregation, recoil implantation and cascade mixing. 

Runs are made to compare the dynamic and steady-state performance of the two alternative control structures (temperature control and cascade composition/temperature control) with the R/F and QR/F ratio installed. The column is subjected to disturbances in feed flow rate and then feed composition. 

The strategy of distillation control is open to many creative approaches because there are five or six main variables to manipulate and many possibilities for cascade, feed-forward ratios, and model-based computer control as well as conventional feedback control. 

Multielement control occurs when two or more input signals jointly affect the action of the control system. Examples of multielement control are cascade control, ratio control, and override control. 

Artificial cascades performed with isolated enzymes in vitro (cell-free extracts or purified enzymes) provide several advantages compared to artificial cascades in recombinant cells. Multi-enzyme reactions based on isolated enzymes can easily be controlled in a desired maimer, including key factors such as enzyme combination in defined ratios and adjustment of specific reaction component ratios (i.e., cofactors). This allows a more detailed control of the biocatalytic multi-enzyme system in contrast to in vivo cascades where the above-mentioned factors are much more difficult to control. 

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