Control secondary measurements

SPS = secondary control variable setpoint and PVS = secondary control variable measurement. The + and — indicate to multiply the signal by +1 or —1... 

Explain what primary and secondary measures are in the context of environmental pollution control. 

The sample of desorbed tritide is placed inside a quartz tube that is connected to a gas-handling manifold by a TorrSeal . A quartz sleeve with Silicon Carbide (SiC) in the annular space is placed around the end of the quartz tube, surrounding the sample with microwave susceptor. The quartz tube and susceptor sleeve are thermally insulated from the rest of the microwave cavity. An internal thermocouple measures the temperature of the sample and provides the temperature signal for process control of the desired temperature. A shine block (alumina foam), attached to the thermocouple, blocks radiant heating of the TorrSeal and the upper area of the quartz tube and manifold. An IR pyrometer is used as a secondary measure of the temperature of the susceptor, and therefore of the sample. A stainless steel shield reflects microwaves from the quartz tube not in the susceptor sleeve, eliminating the production of a plasma at low pressure in the quartz tube. 

For either plant type, incineration, or fuel type, these factors must be empirically determined and controlled. Because dioxins as effluents are concerned, it is possible to reduce I-TE values from about 50 ng/m to about 1 ng/m. Additional secondary measures (filter techniques) are therefore necessary for obtaining the lower limit value of 0.1 ng/m. Secondary measures are special filter techniques for pollutants formed in nongreen processes, also called end-of-pipe technology. The main part of technical incineration plants consists of filter devices, mostly coke as adsorbent is used, which must be decontaminated later by itself by burning in hazardous-waste incinerators. The inhibition technology, discussed later, is related on principles of primary (green) measures for a clean incineration method. 

The control of NO from stationary sources includes techniques of modification of the combustion stage (primary measures) and treatment of the effluent gases (secondary measures). The use oflow-temperature NO,.burners, over fire air (OFA), fiue gas recirculation, fuel reburning, staged combustion and water or steam injection are examples of primary measures they are preliminarily attempted, extensively applied and guarantee NO reduction levels of the order of 50% and more. However, they typically do not fit the most stringent emission standards so that secondary measures or flue gas treatment methods must also be applied. 

When thermodynamics or physics relates secondary measurements to product quality, it is easy to use secondary measurements to infer the effects of process disturbances upon product quality. When such a relation does not exist, however, one needs a solid knowledge of process operation to infer product quality from secondary measurements. This knowledge can be codified as a process model relating secondary to primary measurements. These strategies are within the domain of model-based control Dynamic Matrix Control (DMC), Model Algorithmic Control (MAC), Internal Model Control (IMC), and Model Predictive Control (MPC—perhaps the broadest of model-based control strategies). 

Parallel reactions play an important role in chemical reaction systems that involve selectivity. An example is the selective noncatalytic reduction of NO (SNCR), which is a widespread secondary measure for NO control. In this process NO is reduced to N2 by injection of a reducing agent such as NH3 into the flue gas in a narrow temperature range around 1000°C. The process is characterized by a selectivity in the reaction pathways as shown by the parallel (global) steps... 

Emissions of nitrogen oxides and sulfur oxides from combustion systems constitute important environmental concerns. Sulfur oxides (SO ), formed from fuel-bound sulfur during oxidation, are largely unaffected by combustion reaction conditions, and need to be controlled by secondary measures. In contrast, nitrogen oxides (NO ) may be controlled by modification of the combustion process, and this fact has been an important incentive to study nitrogen chemistry. Below we briefly discuss the important mechanisms for NO formation and destruction. A more thorough treatment of nitrogen chemistry can be found in the literature (e.g., Refs. [39,138,149,274]). 

There are many control challenges in this process. These include strong nonlinearity, distributed system, long deadtimes, and a feedstock that varies significantly because of its biological source. The key variable is kappa number (degree of delignifica-tion), which cannot be measured online, so it must be estimated from secondary measurements. 

A disadvantage of feedback controllers is that corrective action is not taken until after the controlled variable deviates from the set point. Cascade control can significantly improve the response to disturbances by employing a second measurement point and a second feedback controller. The secondary measurement is located so that it recognises the upset condition sooner than the controlled variable. Note that the disturbance is not necessarily measured. 

Cascade control is one solution to this problem (see Fig. 8-35). Here the jacket temperature is measured, and an error signal is sent from this point to the coolant control valve this reduces coolant flow, maintaining the heat transfer rate to the reactor at a constant level and rejecting the disturbance. The cascade control configuration will also adjust the setting of the coolant control valve when an error occurs in reactor temperature. The cascade control scheme shown in Fig. 8-35 contains two controllers. The primary controller is the reactor temperature coolant temperature controller. It measures the reactor temperature, compares it to the set point, and computes an output, which is the set point for the coolant flow rate controller. This secondary controller compares the set point to the coolant temperature measurement and adjusts the valve. The principal advantage of cascade control is that the secondary measurement (jacket temperature) is located closer to a potential disturbance in order to improve the closed-loop response. 

Available measurements. For controlled variables that are not directly measurable, measurements have to be inferred by measurements of secondary variables and/or laboratory analysis of samples. Good inference relies on reliable models. In addition, the results of laboratory analysis, usually produced much less frequently than inferential estimates, have to be fused with the inferential estimates produced by secondary measurements. 

Typical laboratory plants can be used for different purposes if equipped accordingly. One example is shown in Figure 28. In this unit, small product quantities can be freeze-dried in ampules, vials, or trays, and also flasks can be connected to it. The laboratory plant as shown in Figure 29 is equipped for multiple purposes Shelves can be cooled down to -35°C for freezing the product. A valve is installed between chamber and condenser. Thus it is possible to measure the sublimation surface temperature by BTM, to determine the end of main drying and to control secondary drying. The pressure can be controlled, the temperature of the shelves or the product can be recorded, and vials can be closed with stoppers. 

Control of other known determinants, such as atopy and smoking, may be considered as a secondary measure. 

The rate coefficients for the secondary-amine reactions were found to be only 17% of those for the primary-amine reaction, thus explaining the residual secondary amine found at the end of cure. This equation was found to explain the development of the main crosslinking site, namely the tertiary-amine site formed on the DDS, corresponding to network interconnection. However, overlaid with the rate equation for chemical conversion that implies that all reagents are accessible to one another is the effect of the development of the network so that the reactions become diffusion-controlled. This is of interest since this means that the rate coefficients now reflect the chemorheology of the system, not just the chemistry. Thus, if and represent the rate coefficients for diffusion and chemical control, the measured rate coefficient, k, will be given by (Cole et ai, 1991)... 

Reaction rates in soils are more complex than those in pure systems. Secondary and side reactions are difficult, if not impossible, to control. The measured reaction order is therefore usually fractional rather than a whole number because other reactions are usually going on at rates different from the one in question. If only the total change of a component is measurable, the overall reaction rate and order are weighted according to the relative contribution of each reaction. 

It sometimes happens that our control objectives are not measurable quantities that is, they belong to the class of unmeasured outputs. In such cases we must measure other variables which can be measured easily and reliably. Such supporting measurements are called secondary measurements. 

Consider the block diagram of the process shown in Figure 22.6a, with one unmeasured controlled output, y, and one secondary measured output, z. The manipulated variable m and the disturbance d affect both outputs. The disturbance is considered to be unmeasured. The transfer functions in the block diagram indicate the relationships between the various inputs and outputs, and they are assumed to be perfectly known. 

In chemical process control the variable that is most commonly inferred from secondary measurements is composition. This is due to the lack of reliable, rapid, and economical measuring devices for a wide spectrum of chemical systems. Thus inferential control may be used for the control of chemical reactors, distillation columns, and other mass transfer operations such as driers and absorbers. Temperature is the most common secondary measurement used to infer the unmeasured composition. 

Since the feed and overhead compositions are considered unmeasured, we can only use inferential control. The secondary measurement employed to infer the overhead composition is the temperature at the top tray. Let us now examine how we can develop and design the inferential control mechanism. 

Saturation of controllers, 247, 257, 637 Scheduling computer control, 33 Secondary loop, cascade control, 395, 397, 398-99, 400-2 Secondary measurements, 16, 16-18 Second-order system, 186-87 Bode diagrams, 328-30 with dead time, 215, 216 discrete-time model, 585-86 dynamic characteristics, 187-93 experimental parameter identification, 233,668... 

Inferential control configuration uses secondary measurements (because the controlled variables cannot be measured) to adjust the values of the manipulated variables (Figure 2.4). The objective here is to keep the (unmeasured) controlled variables at desired levels. 

Outputs overhead propane composition (unmeasured controlled output) and temperature of top tray (secondary measurement)... 

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