Composite control action

Composite Control Action. Composite control actions are also possible, i.e. P, PI or PD, as well as PID. The most common is PI as P alone will have an offset and the derivative action in PID or PD can introduce unnecessary instability in the response. 

Effect of Composite Control Actions 277 Things to Think About 279... 

The objective of control is quite different. The purpose of control is to keep a process property, e.g. the composition, as close to a preset value as is technically possible and economically desirable. The deviation from the set point is caused by intentional or random fluctuations of the process condition. In order to control the fluctuating process, samples must be taken with such frequency and analyzed with such reproducibility and speed that the process condition can be reconstructed. From this reconstruction predictions can be made for the near future and control action can be optimal. Another goal can be the detection of nonrandom deviations, like drift or cyclic variations. This also sets the conditions for sampling frequency and sample size. 

Cis-acting DNA elements can he near the start site of transcription or be quite distanced from it. Fmthermore, there are examples among eucaryotes in which the cis element is foimd within the transcribed region. If the cis element is located far from the site of action and its effect is also orientation-independent, then it is termed an enhancer. Fmthermore, one frequently observes in eucaryotes so called composite control regions which contain various cis elements. In this case, several transcription factors act cooperatively in the initiation of transcription. Examples for such cooperative effects are observed among the genes controlled by nuclear receptors. 

Figure 2.9 Composite control relies on separate, coordinated fast and slow controllers, designed on the basis of the respective reduced-order models, to compute a control action that is consistent with the dynamic behavior of two-time-scale systems.

Section 2.2, in that two layers of control action involving separate controllers are proposed, whereas composite control relies on a single (possibly multivariable) controller with two components, a fast one and a slow one. Thus, the hierarchical control structure accounts for the separation of the flow rates of the process streams into two groups of inputs that act upon the dynamics in the different time scales. On the other hand, composite controller design (Figure 2.9) presupposes that the available manipulated inputs impact both the fast and the slow dynamics and relies on one set of inputs to regulate both components of the system dynamics. 

Initially use proportional-only controllers in all loops except flow7 controllers, where the normal tight tuning can be used K = 0.5 and T = 0.3 minutes). Set the gains in all level controllers (except reactors) equal to 2. Adjust the temperature, pressure, and composition controller gains by trial and error to see if you can line out the system with the proposed control structure. If P-only control cannot be made to work, PI will not w7ork either. When stable operation is achieved, add a little reset action to each PI controller (one at a time) to pull the process into the setpoint values. 

Experimental System The copolymerisation of styrene with methyl acrylate in toluene using azo-bis-iso- butyronitrile (AIBN) was selected as the model experimental system because the overall rate of reaction is relatively fast, copolymer analysis is relatively simple using a variety of techniques and the appropriate kinetic and physical constants are available in the literature. This monomer combination also has suitable reactivity ratios (i = 0.76 and r4 =0.175 at 80 C),(18) making control action essential for many different values if compositionally homogeneous polymers are to be prepared at higher conversions in a semi-batch reactor. 

PID controllers are useful for certain sluggish processes. Typical applications are temperature control and composition control. A sluggish process often has a tendency to cycle under PI control due to inertia therefore, derivative action tends to reduce the tendency to cycling and allows more proportional action to be used, both of which contribute to improved control performance. A key issue here is to determine whether a process is sluggish enough to warrant a PID controller. Assume that an FOPDT model has been fit to an open-loop step test. If the resulting deadtime, 0, and time constant, x, are such that... 

Suppose that we want to control the composition of the bottoms product by manipulating the steam in the reboiler. This control action will affect the composition of the overhead product (A + B), which in turn will affect the reaction conversion in the CSTR. 

It is important to note that the behaviour of these steady states is not identical with respect to inherent disturbances in operating conditions, as for example feed reactor temperature, composition or flow rate of the feed, or temperature and flow rate of the cooling agent, etc. Some are insensitive to such variations, in the sense that after the disturbance vanishes the system comes back naturally in the original state. These are stable stationary states, as the points A and C in Fig. 8.17. In the case of the point B the situation is essentially different. This is an unstable stationary state because in the absence of a control action small disturbances will move the system either to the high conversion state (reaction ignition), or to the low conversion state (reaction extinction). This type of behaviour is dangerous for operation and must be avoided. 

The net result of the control action is a shift in the material balance, so that more of the feed leaves with the distillate and less with the bottom. The shift transports the light component up the column and keeps bottom (and therefore, top) composition constant. 

Sluggishness and oscillations in boilup regulation are far more potent and interactive when boilup is manipulated to achieve a desired product purity than when boilup is kept constant. This is because the temperature or composition controller feeds back any fluctuations in boilup manipulation as delayed signals calling for further manipulative actions. The author experienced a case where this feedback action rendered a sluggish boilup control system inoperable during even mild upsets. 

Figure 18.3 shows examples of applying this procedure to benzene-toluene columns with different feed points and different feed compositions. Accordingly, trays 7,10, and 5 or 10 are the best control trays in Fig. 18.3a, b, and c, respectively. Figure 18.4, based on the column in Fig. 18.3a, shows how a variation in control tray temperature affects product composition with a correctly located and an incorrectly located control tray. When the temperature variation is caused by a change of pressure or in the concentration of a nonkey component, it will produce a steady-state offset in product composition. A disturbance in the material or energy balance will cause a similar temperature variation until corrected by the control action in this case, the offset will only be temporary. Figure 18.4 shows that the offset in either case is minimized when the control tray is selected in accordance with Tolliver and McCune s procedure (403). A dynamic analysis by these authors (403) indicated that the control tray thus selected tends to have the fastest, most linear dynamics. 

The success of the differential temperature control technique depends on finding a suitable second temperature. If none of the products is relatively pure, such a point may not be found (418), and this technique may be troublesome. Figure 18.86 shows the behavior of a differential temperature controller in the deisobutanizer (Fig. 18.8a) described by Webber (418). When the bottom product is relatively pure (to the left of the maximum in Fig. 18.86), the controller functions normally. A fall in differential temperature signals depletion of lights in the bottom, the controller will reduce boilup, and both the differential temperature and the bottom composition will rise and return to their desired values. The same control action to the right of the maximum (Fig. 18.86) will reduce the differential temperature, which in turn will further lower boilup, and so on, causing a "runaway rise in the bottom lights content. 

In Vermilion s case, the light key content of the bottom product was about 5 percent, and operation was maintained to the right of the maximum (411) this is the reverse of Webber s case (418). During one period, at which the light key content was lowered to 2 percent, the same control system worked well after control valve action was reversed. Vermilion reported stable and accurate composition control with his scheme. "Bouncing across the maximum only occurred at startups and in major upsets (411). 

The problem has been viewed in this chapter as one of estimating the composition of the light-key component on a tray by measuring both the temperature and the pressure. The resulting controller is a light-key composition controller and has Direct action. We could alternatively choose to estimate the heavy-key composition, in which case the composition controller would have Reverse action. 

Normally, one would seleet a temperature target such that the bottom composition is as close to the speeifieation limit as possible. There will always be some variability in the control performance due to external disturbances and limitations on loop control action. If composition control is poor and has a high variance, the observed composition probability distribution could look like a normal distribution in relation to operating margin as shown in Figure 14.3. More detailed explanation for using normal distribution to represent operating data can be found in Chapter 4. 

While there are temperatures with very short deadtimes there will be other measurements that, under certain circumstances, show long deadtimes. In Chapter 4 we include a level control configuration that is likely to benefit from derivative action. In Chapter 7 we describe a composition control strategy with a very large OIr ratio. 

We have seen that the Ryskamp scheme largely breaks the interaction in one direction so that corrections made to the bottoms composition have little impact on the distillate. Although the converse is not true an adjustment to the reflux ratio will affect the bottoms composition, but when its controller takes corrective action it will not light the distillate composition controller. 

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