Computed Variable Control

One of the most logical and earliest extensions of conventional control was the idea of controlling the variable that was of real interest by computing its value from other measurements. 

For example, suppose we want to control the mass flow rate of a gas. Controlling the pressure drop over the orifice plate gives only an approximate mass flow rate because gas density varies with temperature and pressure in the line. By measuring temperature, pressure, and orifice-plate pressure drop, and feeding these signals into a mass-flow-rate computer, the mass flow rate can be controlled as sketched in Fig. 8.3a. 

Another example is sketched in Fig. 8.3i . A hot oil stream is used to reboil a distillation column. Controlling the flow rate of the hot oil does not guarantee a fixed heat input because the inlet oil temperature can vary and the AT requirements in the reboiler can change. The heat input Q can be computed from the flow rate and the inlet and outlet temperatures, and this Q can then be controlled. 

As a final example, consider the problem of controlling the temperature in a distillation column where significant pressure changes occur. We really want to measure and control composition, but tmperature is used to infer composition because temperature measurements are much more reliable and inexpensive than composition measurements. 

In- a binary system, composition depends only on pressure and temperature  

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A host of gadgets and software are available to perform a variety of computations and logical operations with control signals. For example, adders, multipliers, dividers, low selectors, high selectors, high limiters, low limiters, and square-root extractors can all be implemented in both analog and computer systems. They are widely used in ratio control, in computed variable control, in feedforward control, and in override control. These will be discussed in the next chapter. 

Computed variable control, (a) Maas flow rate (b) heat input (c) composition (piessure-compcnBated temperature). 

Computed variable control, (a) Mass flow rate, (b) Heat input, (c) Composition (pressure-compensated temperature). 

With a host computer allows moving on to advanced control and multi-variable control. The unit is sensitive to day/night temperature swings and the multi-variable control can track ambient changes. 

Instrumentation is also fitted to provide a continuous display of important variables such as temperature and pH, the power used hy the electric motor, airflow, dissolved oxygen and exhaust gas analysis. Manual or computer feedback control can be based either directly on the signals provided hy the prohes and sensors or on derived data calculated from those signals, such as the respiratory coefficient or the rate of change of pH. Mass spectronomical analysis of exhaust gases can provide valuable physiological information. 

To consider pH as a controlled variable, we use a pH electrode to measure its value and, with a transmitter, send the signal to a controller, which can be a little black box or a computer. The controller takes in the pH value and compares it with the desired pH, what we call the set point or reference. If the values are not the same, there is an error, and the controller makes proper adjustments by manipulating the acid or the base pump—the actuator.2 The adjustment is based on calculations using a control algorithm, also called the control law. The error is calculated at the summing point where we take the desired pH minus the measured pH. Because of how we calculate the error, this is a negative feedback mechanism. 

The ideal variable to measure is one that can be monitored easily, inexpensively, quickly, and accurately. The variables that usually meet these qualifications are pressure, temperature, level, voltage, speed, and weight. When possible the values of other variables are obtained from measurements of these variables. For example, the flow rate of a stream is often determined by measuring the pressure difference across a constriction in a pipeline. However, the correlation between pressure drop and flow is also affected by changes in fluid density, pressure, and composition. If a more accurate measurement is desired the temperature, pressure, and composition may also be measured and a correction applied to the value obtained solely from the pressure difference. To do this would require the addition of an analog or digital computer to control scheme, as well as additional sensing devices. This would mean a considerable increase in cost and complexity, which is unwarranted unless the increase in accuracy is demanded. 

The use of computers to control all of the variables during mixing can give greater batch consistency than the less sophisticated control strategies. 

Thirty years ago these computed variables were calculated using pneumatic devices. Today they are much more easily done in the digital control computer. Much more complex types of computed variables can now be calculated. Several variables of a process can be measured and all the other variables can be calculated from a rigorous model of the process. For example, the nearness to flooding in distillation columns can be calculated from heat input, feed flow rate, and... 

During the last two or three decades, chemists became used to the application of computers to control their instruments, develop analytical methods, analyse data and, consequently, to apply different statistical methods to explore multivariate correlations between one or more output(s) (e.g. concentration of an analyte) and a set of input variables (e.g. atomic intensities, absorbances). 

MFC control approach shows its incentives over the classical decentralized FI control due to the intrinsic capability of counteracting interactions between controlled variables, the use of future process behaviour predictions for computing the control actions, the straightforward implementation of the combined feedforward-fedback control setup, the capability of systematic constraints handling and its optimal feature, all as a result of directly involving the process model in the MFC control law. 

Some variability in the flow curves of the different valves is also noted in Fig. 17.6. A level of discrepancy is expected for the first generation, prototype valve, and the variability would be reduced with changes in the manufacturing process for production valves. For rig testing, the variability can be accommodated with the computer-based control system. 

A modem apparatus is usually equipped with a computer that can calculate the weight loss fraction or percentage. A commercial TGA is capable of greater than 1,000°C, 0.1 pg balance sensitivity and variable controlled heat-up rate under an atmosphere of air or another gas. The heat-up rate capability of TGA can vary from 0. l°C-200°C/min. 

A feedforward controller can be used to transport information already available somewhere to other place in the flowsheet. Figure 3.21 displays a typical implementation. Flere the controller sets a downstream sampled variable at a given value based on an upstream computed variable. 

Scaling of variables and disturbances. Proper scaling is necessary for a meaningful computation of controllability indices. 

Modem switchgear and variable speed controllers are available with micro-computer based control, protective and indication facilities. These can communicate between each other and to external networks by such links as fibre optics and digital hardwire networks. 

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