EXAMPLE 1.1 Before the advent of instrumentation science, control action was
and also in a fair number of industries. The study of such a system may give us an opportunity to compare part by part with that of an instrumental control. Figure 1.5 depicts a human being riding a bicycle.
Figure 1.5 A man riding a bicycle and trying to advance on an imaginary straight line.
The rider looks ahead and receives information about his current position (Controlled Variable) and also about the imaginary dotted line (Set Point). So obviously the eye acts as the Sensor, that sends the information to the human brain (the Controller), and after processing the data, the decision or control action is achieved by steering the bicycle by the rider’s hand (Final Control Element).
Note that a person, who has just learnt how to ride a cycle, gradually increases his skill as he continues the practice. From his initial failures and incompetence, he picks up what are the dos and do-nots about cycle riding. The controller stores this information, putting more importance (weight) on the ‘do-list’. Thus, an efficient control strategy grows up.
Is it possible to artificially build up such a self-learning intelligent controller?
EXAMPLE 1.2 The control system, called Fly-ball Governor, was probably
developed as one of the first of its kind, which was successfully used in industrial application for more than a century. The principal purpose of a Governor is to maintain rotational speed of a steam turbine.
The operation of this control system is simple; the assembly of the twin mass and linkage mechanism rotates with the turbine through a gear and pulley and rides on a free sleeve over the vertical stem. The steady rotational speed of the turbine may change due to load change as well as inlet steam pressure variation. This will cause the spherical masses to come closer or move away as the centrifugal forces decreases or increases until a new balance point is reached with the compressed spring. Thus the vertical stem goes upward or downward. The valve-plug attached with the stem will move away or come closer to the valve-seat, causing the steam flow to vary in a
manner so that the turbine speed comes back to its desirable value.
Figure 1.6 illustrates the action of such a Governor. Adjusting the spring compression may change the desired speed or set point of this control system. A higher compression will raise the set point to higher speed.
Figure 1.6 The steam governor probably the oldest controller.
There is no historical information available about the inventor of this machine; it was used in the industry for a very long time probably from the period when the first development of steam engine was going on during industrial revolution. There was no analytical or design data available and a small bunch of senior mechanics could build Governors by experience only. Then in 1868, Maxwell published a paper, in which he put forward the complete analysis of this machine, and probably started the era of an analytical way of control system analysis and design.
EXAMPLE 1.3 Probably not so historical but much more popular and in current use
is the Float type Liquid Level Controller (Figure 1.7).
Figure 1.7 The float type level controller.
A rise in liquid level causes the hollow Ball–Float to lift, and the attached ‘plug’ of a valve mechanism comes closer to its ‘seat’ (built on the end of the liquid inlet) to reduce the liquid inflow. This system has a similarity with the Governor of Example 1.2, in the fact that inception of this level control system also has been lost from
annuls of technology development. In the system, the set point is the location of the hinge on the tank wall which is usually fixed because in major number of applications it is required that the tank should be filled to the fullest before use.
EXAMPLE 1.4 This is an example from a typical mechanical operation: rolling of a
thick metal sheet as feed into a thinner sheet as a product of controlled thickness. Product thickness is measured by measuring the intensity of the g-ray beam coming through the product from a radioactive source.
The source (a typical source may be the radio-isotope of Cobalt with an atomic number–60), detector and the associated electronics that interprets the beam intensity in terms of sheet thickness, constitute the measuring system. The measured value of the product sheet as a current signal is transmitted to the thickness controller that compares the thickness with the set value, finds the error, and computes corrective action as its output as a current signal. A typical set of electronic control hardware may operate within an input/output range specification of
4–20 mA DC. Controller output, as current signal is converted to hydraulic fluid pressure in a Signal Transducer, is symbolically represented by ‘I/P inside a circle’ as standard P&I drawing symbol, as illustrated in Figure 1.8.
Figure 1.8 The thickness control of a metal sheet rolling system.
In case the manufactured sheet is of incorrect thickness, the change in fluid pressure is amplified in a hydraulic actuator. We get a vertical displacement of the lower roller as the piston works and comes in balance with the spring force, and the gap between two rollers is suitably adjusted to obtain a metal sheet of correct thickness. This arrangement may be called the Final Control Element (FCE) of the control system.
The Thickness Control System looks apparently fine. But an interesting question crops up. Any defective portion of the sheet has to travel the distance from the Roller assembly to the detecting point before the defect is sensed, and at each of these instance the smallest length of defective thickness is at least equal to the distance between roller and thickness detector. Note that we have no information about the
thickness of the sheet during the ‘time’ when it travels between the production and detection point. Let us call this phenomenon Dead time because we are completely unaware of what is happening at the process output during this time. The information currently available from the sensor has actually happened in the past or earlier by an amount equal to the dead time of the system. Please remember that this delay or dead time poses a serious problem in control system design as we have seen here. We shall have to talk about these delays in proper time, in detail, in further chapters.
EXAMPLE 1.5 In this example we demonstrate the control of the exit liquid stream
temperature from a constant hold up mixer cum heater (Figure 1.9). This is one of the most popular example systems that have been used in numerous texts to introduce many important conceptions of control engineering. We shall also do so in our discussions.
Figure 1.9 The temperature control system of a mixer pre-heater.
A Thermocouple Sensor, TC, measures the exit stream temperature, TC. The TC output is electronically conditioned in the Temperature Transmitter, TT, to 4–20 mA DC current signal and transmitted as the measured variable, TM, to the Temperature Indicator Controller, TIC. Such a Controller, beside its control capability has the facility of displaying the Measured Variable, TM, and Set value, TR. Error is found as,
e = TR – TM, and the Controller Output, CO, is produced as a function of error, CO = f[e(t)]. The low energy output from the Controller is amplified through the FCE
(which may be a Thyristor type power regulator) that changes the power mains (230 V) current to the resistance heater in the tank.
There are many industrial applications of this system. For instance, furnace oil (FO) is a commercially available liquid fuel used in furnaces. At normal temperature, FO is a thick liquid with waxy and tarry particulate deposits that reduce its flow-ability. This oil has to be heated to about 90°C–100°C before it is sent to the burner. On the other hand, over heating of FO may raise some of its lighter components to their ignition temperature and cause fire hazards. Hence, temperature control of the exit liquid from
the pre-heater is needed to have an uninterrupted flow of FO and furnace operation. The thermal quality of feed stream to a distillation column needs to be uniform and as close to the design specification of the feed as possible, because otherwise the column may become unbalanced. A temperature controlled feed pre-heating system is again the answer to such an application.
The next three examples have been chosen to introduce some new aspects of process operation problems, and also because they have been addressed by realization of control system.
EXAMPLE 1.6 A tank acts as a constant head reservoir for supplying liquid to a
process. The process has variable demands. A Constant head in the tank is required so that exit flow rate is only dependent on the resistance in the outflow line. The resistance may be the Control Valve (FCE) of the control system of the down stream process. The liquid level of the tank is measured by a level sensor-transmitter, and sent to the level Controller. The Controller Output manipulates inflow through the Control Valve. The open loop process, and the process with its control system has been shown in Figure 1.10.
Figure 1.10 The dynamic level system and its control.
EXAMPLE 1.7 In a distillation column, the reflux ratio is one of most important
parameters to be maintained to keep up the top product or distillate composition to the desired value; and in many instances top product is the desired product of this operation. Reflux ratio, as the name suggests, is the ratio of molal or mass flow rates of two streams R and D.
Figure 1.11 The reflux ratio control of a distillation column.
The Total Condenser condenses all the vapours coming from the top plate of the column. The condensed liquid is diverted into two streams, R and D. R is fed back to the top plate, and D is the product stream. A composition sensor-transmitter on the product line measures the product composition and sends the information to the composition Controller, which manipulates the reflux ratio through the three-way control valve. Figure 1.11 depicts the control system.
[Three way Control Valves are a variety of control valves and acts as special final control elements. They come in two basic configurations: (1) Diverting type has one inlet and two outlet ports. Liquid coming through inlet goes out through the outlet ports subdivided into two streams at a definite volume ratio. This ratio is dependent on the valve stem position. (2) Mixing type has one outlet and two inlet ports. Liquids coming through inlet ports are mixed in a definite volume ratio inside the valve body, and go out through the outlet port. Again this ratio is dependent on the valve stem position.]
The same control action may be achieved by using two sets of two-way Control Valves. But discussion on this topic should be made after the Action of a Control Valve is introduced in Chapter 7.
EXAMPLE 1.8 In many process industries, including production of heavy chemicals,
steel, aluminum, and fertilizers, where high pressure steam is used as a reaction component or utility at certain stages of manufacture, high temperature saturated water or aqueous solution streams containing mineral solutes are produced as a by-product.
Such a stream contains a large amount of energy. Unless this energy is recovered, the production economics becomes very poor. Recovery through heat exchangers by heating an incoming cold liquid is less efficient than ‘Flashing’ operation. Flashing of a high temperature high-pressure liquid means suddenly expanding it in a low- pressure chamber where the stream will separate into saturated vapour (relatively low pressure pure steam) and saturated liquid fractions.
Then the generated steam may be put into the medium pressure steam supply line and the liquid sent either to the next flashing stage or to a heat exchanger. Successful operation of a flashing stage requires that the chamber is maintained at a slightly higher pressure than the medium pressure steam header, and a positive liquid head has to be kept so that full flow of liquid occurs through the liquid outlet of the flashing unit.
A control system has been illustrated in Figure 1.12, for this purpose. Note that in this system there are two Controlled Variables involved in the same process. If physical laws relate these variables to each other, a situation may arise when manipulation in one loop may affect the second loop so that the second Controlled Variable is disturbed from its set value. This is one of the classical problems associated with multivariable control systems, known as variable interaction or simply interaction. We have many things to talk about interaction but only when we start our discussion on multivariable system. It is sufficient to comment here that in this example the loops have very negligible interaction and cause no operational problem as such.
Figure 1.12 Multi-loop control system of a flashing stage.
Still, there is a possibility of another kind of control difficulty about which you should be aware of. It is very usual in a plant that there are few load or demand points connected in a parallel fashion to the steam line, and they have their own on-off schedule. This will cause fluctuation of pressure in the steam line. Now you may appreciate the difficulty that such a pressure fluctuation will bring into the pressure control loop of the Flashing Stage. This problem will be tackled when we discuss about Cascade Control.
To appreciate the existence of control action in areas other than technology and science, we cite the following two examples.
EXAMPLE 1.9 An advanced diabetic patient needs to be injected with insulin
regularly round the clock depending on his fluctuating blood sugar level. A special needle like glass electrode (marketed by Pyrex Corpn.) inserted in an artery of the patient continuously measures the blood sugar level, and transmits the information to the Controller. A microcomputer based concentration controller computes the amount of insulin to be injected, with respect to current sugar level.
The final control element of this control system is a special pump known as Peristaltic
Pump through which Insulin is injected. A portable version of this machine is also available. Figure 1.13 presents the system.
Figure 1.13 The blood sugar level control system of an advanced diabetic patient.
EXAMPLE 1.10 An example from a socio-political system should be a proper ending
of this section. An army General has become the Dictator (Controller) of the state. He wants to maintain a particular type of condition (Set Point) in the country. He has no real communication with his countrymen.
His only way to know about the real state of affairs (Controlled Variable) is the information received from certain gentlemen (sensor-transmitter) who generally perform night duties under his employment (Figure 1.14). They wear low hats, black goggle, long coats with upturned collars and are known only by numerals starting with double zeros.
Figure 1.14 Control of a state under a dictator.
But currently (for t 0) the information received about the Controlled Variable value has been very disturbing, and quite deviant from the set point value. The Controller has five alternative control actions:
1. A statewide civil action by employing police, armed police, militia forces (FCE is the Home Ministry).
2. A statewide military action by employing the State Guards, and regular Army divisions with an air cover (FCE is the Defense Ministry).
3. One specially chosen gentleman he is equipped with a long range target rifle mounted with a high power scope and made to stay in front of the rebel’s house (FCE is the Department of Covert Operations).
4. Breaking out a war with a neighbouring country, and trying to convince the people that all their hardships are due to the aggressive attitude of the neighbour (FCE is the Information and Cultural Ministry).
5. The dictator, using a disguise, mixes with his countrymen to know about their grievances like the famous emperor Harun-all-Rashid, and removes the socio- political dirt. Well, this control action is an idealistic utopia that never happens.