Applying Feedforward Control

Feedback control of product quality from a column is not always satisfactory even when the control loops are properly arranged. Proper arrangement only protects the process from upsets in heat input, feed enthalpy, and reflux flow and enthalpy. The most significant disturbances to quality control are generally variations in feed rate and composition. 

From the previous example, it was pointed out that a composition controller may need a proportional band as high as 1,000 percent. And because the period of the closed loop may be from 20 min to 2 hr, reset time of 10 min to 1 hr is commonly encountered. The integrated error caused by a load change was shown earlier to equal the product of the proportional band times reset time. Distillation is characterized by a large proportional-reset, product , compared to other processes. And because integrated error in product quality can be costly, distillation is a prime candidate for feedforward control. 

An on line analysis of product composition is not always available. In these instances, there is no measurement to feedback from, so a forward loop can be a great help in maintaining control in the face of disturbances. Furthermore, if the real controlled variable is profit or loss, an optimum control program can be based on a feedforward model. Consequently the feedforward approach to control is of utmost importance in distillation processes, whatever the nature of the separation. 

The basis for feedforward control of any mass transfer operation is the material balance. Earlier in this chapter the distillate to feed ratio was shown to be the principal factor affecting composition of either product stream. The feedforward control model is nothing more than an on-line solution to the material balance  

Distillate rate is the manipulated variable feed rate F is one component of load and feed composition z is the other. Either distillate composition y, or bottoms composition x is the set point, while the other depends on separation. 

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An illustration of the use of chromatography in this industry is in the control of distillation towers. Distillation uses the difference in composition between a liquid and the vapor formed from that liquid as the basis for separation. The efficiency of the process is affected by temperature, pressure, feed composition, and feed flow-rate. Chromatography is used to monitor the composition of the feedstock and to apply feedforward control of the heat input (temperature) to the tower, or to monitor and control the composition of the product. In this latter case, the chromatograph output is simply compared with a set point, and the controller (using feedback) manipulates the temperature, pressure, or feed flow-rate by activating the appropriate final operator. Both types of distillation control are widely employed in petroleum refining. 

Apparently, an important point has been overlooked— namely, that the recycle stream consists of the same flow of B + D that leaves the reactor. Because this material simply recirculates and does not participate in the reaction process under steady-state operating conditions, it should be ignored in applying feedforward control of the ratio. Often, a recombination of variables can lead to a less coupled system, as shown in Chapter 18 and, again, with the addition of simple ratio control between the B and A feed streams in the case study. That is not the situation for the combined B flow rate. 

Feedforward control can also be applied by multiplying the liquid flow measurement—after dynamic compensation—by the output of the temperature controller, the result used to set steam flow in cascade. Feedforward is capable of a reduction in integrated error as much as a hundredfold but requires the use of a steam-flow loop and dynamic compensator to approach this. 

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

In the last chapter we used Laplace-domain techniques to study the dynamics and stability of simple closedloop control systems. In this chapter we want to apply these same methods to more complex systems cascade control, feedforward control, openloop unstable processes, and processes with inverse response. Finally we will discuss an alternative way to look at controller design that is called model-based control. 

The line diagram in Figure 48 is employed to maintain the appropriate flowrate. Feedforward control is applied. 

Figure 15.54b is a schematic of a feedforward controller applied for steam drum level control. If the flow rate of the makeup feedwater is equal to the steam usage, the drum level remains constant. One is tempted to conclude that the feedforward controller is aU that is needed for this application. Unfortunately, the measurements of the steam usage and the feedwater flow rate are not perfectly accurate. Even small errors in measured flow rates add up over time, leading to one of two undesirable extremes. The drum can till with water and put water into the steam system, or the liquid level can drop, exposing the boiler tubes, which can damage them. As a result, neither feedback nor feedforward are effective by themselves for this case. In general, feedforward-only controllers are susceptible to measurement errors and umneasured disturbances, and, as a result, some type of feedback correction is typically required. 

By analyzing the dynamic mismatch, adjust 0. The direction of the deviation should indicate whether the feedforward correction is applied too soon or too late, causing dynamic mismatch. Figure 15.55b shows the feedforward control performance after 0 is tuned. 

The exponential term implies that we need future values of the disturbance in order to compute the current value of the manipulated variable. But, such future values of the disturbance cannot be available. In such case the feedforward controller, described by the last equation above, is characterized as physically unrealizable and cannot be applied in real situations. 

The two basic types of control loops applied to automated systems are termed feedback and feedforward, and are shown in Figure 24.3. The fundamental difference between these two types lies in the position of the measuring instrument. In feedback control, the measurement is performed either within or at the output of the process, and deviation from the set point causes an operation at the process input. Thus, an error must occur before corrective action can be initiated. In feedforward control, measurement is made at the input to the process, and any deviation from the set point is fed forward to initiate corrective action prior to occurrence of the error. Thus, feedforward systems are theoretically capable of perfect control. 

Figure 24.3. Feedback and feedforward control systems. In feedback control, a measuring instrument obtains information at the output of a process, the signal obtained is compared to a set point, and the difference (or result) is applied to a final actuator. The result is ultimately detected by the measuring instrument and closed-loop control results. In feedforward control a measuring instrument obtains information at the input of a process, the signal obtained is again compared to a set point, but now the result is applied to an actuator that controls another input to the process. The result is not detected by the measuring instrument and open-loop control results. Courtesy of the Foxboro Company.

At the lowest level, skill-based behavior, human performance is governed by patterns of preprogrammed behaviors represented as analog structures in a time-space domain in human memory. This mode of behavior is characteristic of well-practiced and routine situations whereby open-loop or feedforward control makes performance faster. Skill-based behavior is the result of extensive practice where people develop a repertoire of cue-response patterns suited to specific situations. When a familiar situation is recognized, a response is activated, tailored, and applied to the situation. Neither any conscious analysis of the situation nor any sort of deliberation of alternative solutions is required. 

A different type of closed-loop control is feedforward control, in which optimal controls are explicitly obtained in advance from the inputs in conjunction with the mathematical model of a system. As shown in the above figure, feedforward controls are applied to the system without having to wait for the system state the inputs and controls would later generate. 

In food supply networks, causes of deviations may reside in many aspects, for example, mistakes by operators, or biological variation of primary products. If feedback control is applied for deviations in food supply networks, production can only be influenced after losses have aheady been incurred. To prevent deviations from happening, it is necessary to reahze feedforward control for deviations in food supply networks. 

Feedforward control is often undervalued or left to the MVC. Chapter 6 shows how simple techniques, applied to few key variables, can improve process stability far more effectively than MVC. 

Due to the above-mentioned difficulties with manual and temperature-based feedback controllers, the control systems based on product moisture content have been investigated and applied in many graindrying installations in recent years. Forbes et al. compared different control strategies based on the product moisture content for commercial corn-drying units [49]. Three control schemes were studied (1) a model-based feedforward controller for which the corn-drying process is represented by an exponential-decay-type model with the corn-drying characteristics lumped into a single parameter (2) a feedback... 

Shinskey, F. G. Feedforward Control Applied, ISA Journal, November, 1963. 

In fact, the compensation shown in Fig. 11.24 can then be achieved with a lag in the forward loop. This is especially desirable when feedforward control is applied to a train of closely coupled towers. 

As mentioned earlier, successful operation of a process requires that key process variables such as flow rates, temperatures, pressures, and compositions be operated at or close to their set points. This Level 3a activity, regulatory control, is achieved by applying standard feedback and feedforward control techniques (Chapters 11-15). If the standard control techniques are not satisfactory, a variety of advanced control techniques are available (Chapters 16-18). In recent years, there has been increased interest in monitoring control system performance (Chapter 21). 

Feedforward control was not widely used in the process industries until the 1960s (Shinskey, 1996). Since then, it has been applied to a wide variety of processes that include boilers, evaporators, solids dryers, direct-fired heaters, and waste neutralization plants (Shinskey et al., 1995). However, the basic concept is much older and was applied as early as 1925 in the three-element level control system for boiler drums. We will use this control application to illustrate the use of feedforward control. 

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. 

We showed through nonlinear dynamic simulations how the process reacts to various disturbances and changes in operating conditions. We have not shown any attempts to optimize process performance, to improve the process design, or to apply any advanced control techniques (model-based, nonlinear, feedforward, valve-position, etc.). These would be the natural next steps after the base-level regulatory control system had been developed to keep the process at a stable desired operating point. 

We had also mentioned previously, that when there is a disturbance, the control does not usually know beforehand how much duty cycle correction to apply. In the lower half of Figure 7-11, we have described an increasingly popular technique being used to make that really happen (when faced with line disturbances). This is called input-voltage/line feedforward, or simply feedforward. ... 

ANN has also been applied to flow control in microfluidic networks. Assadsangabi et al. [13] presented a combined feedback/feedforward strategy to control the output flow rate in the T-juncti(Mi of microchannels. A finite element model (FEM) was used to generate the training data, and a combined ANN and fuzzy logic (FL) system was utilized to build an inverse model of the flow in the T-junction, which serves as a controller to adjust the output flow rate. 

The constructive method, which is considered as a major breakthrough in control theory, was developed in the last decade. As it stands, the method is intended for feedback control design, and its application to the batch motion case requires the nominal output to be tracked and a suitable definition of finite-time batch motion stability. In a more applied eontext, the inverse optimality idea has been applied to design the nominal motion of homo [11] and copolymer [12] reactor, obtaining results that are similar to the ones drawn from direct optimization [4]. The motion was obtained from the recursive application of the process dynamical inverse [13], and the inverse yielded a nonlinear SF controller [9, 10] that was in turn used to specify a conventional feedforward-feedback industrial control scheme. However, the issues of motion stability and systematized search were not formally addressed. 

Feedforward is commonly applied to level control in a drum boiler. Because of the low time constant of the drum, level control is subject to rapid load changes. In addition, constant turbulence prevents the use of a narrow proportional band, because this would cause unacceptable variations in feedwater flow. The feedforward system simply manipulates feedwater flow to equal the rate of steam being withdrawn, since this rqiresents the load on drum level. The system is shown in Fig. 8.2. 

Absorption is not a refining operation and is rarely the last operation conducted on a product. Consequently, close control of the concentration of either effluent stream is not paramount, and on-line analyzers are not often used. More importance is placed on minimizing losses (such as Vy) or total operating costs, for which the simple optimizing feedforward system was designed at the close of Chap. 8. In that example, as in the control equation (12.8), maintenance of a designated ratio of L/F applies. 

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