Computer simulation in process control

Computer simulation in process control

Mathematics and Computers North-Holland in Simulation 259 27 (1985) 259-266 COMPUTER SIMULATION IN PROCESS CONTROL D.W. TYLER and A.K. QUIBELL...

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Mathematics and Computers North-Holland

in Simulation


27 (1985) 259-266






Chisholm Institute of Technology, Caulfield East, and Taylor Instrument

Company, Melbourne, Australia

SUMMARY This paper describes a process control course at Taylor Instrument Pty. Ltd., Melbourne, in which industrial process recording and control hardware is interfaced to computer simulated process plant and instrumentation. A number of process plants are provided in simulated form and five work stations are available. Each station has separate independent control over the simulated process it is accessing, and a variety of changes can be made to the simulated process and instrumentation via an interface box. Each work station is also equipped with a conventional three term PID controller, a micro-processor adaptive gain controller and a four pen recorder. It, therefore, becomes possible to investigate the effectiveness of a variety of control strategies on a wide range of problems typical of those encountered in real process plant.



The way in which process control subjects are presented to undergraduate students in colleges and universities is often criticised by practising engineers as being too divorced from the real world of process control. Traditionally, one way in which this problem is overcome is by carrying out laboratory work using various pieces of equipment and instrumentation. In some instances, the equipment is designed exclusively for educational purposes and, being sometimes quite artificial, can only reinforce the criticism of the engineer in industry. From an educational point of view, there are a number of difficulties. Obviously, experiments based on actual processes would require a variety of real process plants, complete with instrumentation and control equipment. There are many problems including those of safety, cost and space which aggravate the difficulties of this approach. Computer simulation of the process plant and some of the instrumentation can offer a solution to many of these problems. In addition, by interfacing the computer to industrial equipment such as a controller and a recorder, a significant degree of realism can be added, thus largely overcoming the criticism of the practising engineer. In fact, an 037%4754/85/$3.30

0 1985, IMACS/El

operator in the control room of a refinery or a power station may be aware of the plant only through the signals that reach the recorder and controller in the control room. With care, the signals generated by the simulation and used by the controller and recorder can be made to correspond very closely to the real thing. A training system incorporating this approach has been in use at Taylor Instrument Company for some years and, in a more modest way, is being implemented at Chisholm Institute of Technology. The simulations are particularly useful, as they include a variety of nonlinearities typical of those found in actual process plant. In addition, the training system includes a micro-processor adaptive gain controller and this allows the solution of some of the problems introduced by nonlinearities to be investigated. 2.


A common requirement in process control is to ensure that a certain property remains constant in spite of the presence of various load disturbances which tend to cause it to vary. A traditional approach to this problem is to make use of the feedback control loop. A measurement is made of the process property and this measurement is compared with the desired value of the property in a controller.

sevier Science Publishers

B.V. (North-Holland)


D. W. Tyler, A. K. Quibell

/ Computer

A deviation or error signal (equal to the difference between the measurement and desired value) is then used to adjust the process in such a way that the error is reduced. A closed loop is, therefore, produced and this immediately increases the complexity. Processes which were inherently stable can, with the addition of a feedback loop, become unstable. In addition, various pieces of equipment are required in the feedback loop, and these can introduce non-linearities, which makes analysis difficult. A good simulation should model not only the process, but all the relevant characteristics of the equipment in the control loop. 3.


The first simulation is concerned with a simple flow process. Referring to figure 1, upstream and downstream pressure variations can be considered as load disturbances on the flow rate and are provided for in the simulation. Upstream pressure



:f%re? Flow


0 Iprocess


Figure 1: Flow process In order to implement control, a measurement must be made. One of the most commonly used flow measuring elements is the orifice plate, as shown in figure 2. Pressu;rIy



in process


this (often mounted directly on the flow line) as shown in figure 3. Signal to controller

Differential pressure transmitter 0 AL

Figure 3: Differential pressure transmitter Industrial transmitters are generally designed to provide a standard output signal to the controller of 20-100 KPa or 4-20 mA, depending on whether the controller is pneumatic or electronic. Force balance techniques are used in transmitters where the differential pressure from the orifice plate acts across a small diaphragm to develop a force at one end of a beam. The transmitter will generally have zero and span adjustments and may incorporate a square root extraction function to compensate for the squaring produced by the orifice plate. This square root extraction may take place at the controller, or in a separate instrument. Calibrated damping adjustments may also be incorporated in the transmitter. The simulation incorporates a square root function, damping and the span adjustment of the transmitter. The output from the transmitter then becomes the input signal to the controller, as shown in figure 4.

Figure 2: Flow measurement There are some problems in using the orifice plate, namely:(i)

The inherent non-linearity of the orifice plate in that the flow rate is proportional to the square root of the pressure difference.


The spurious noise originating from the random pressure fluctuations at the orifice taps.

The simulation provides for both the inherent non-linearity and the noise of the orifice plate. The next part of the control loop is concerned with getting the measurement signal, in an appropriate form, to the controller. A differential pressure transmitter is used for

Figure 4: Controller At this point in the control loop, actual industrial controller hardware is used - a choice being possible between a conventional 3 term analog controller and a micro-processor adaptive gain controller. The controllers will be discussed in more detail later. The output from the controller is used to

D. W. Tyler, A. K. Quibell / Computer simulation in process control control the position of a valve in the flow line. Since the most commonly used valve actuator is pneumatic, the use of an electronic controller will necessitate an electropneumatic converter, as shown in figure 5.


Double seated valves can be used to minimise the effects of valve plug unbalance. Additional devices may be necessary to minimise other adverse effects. A volume booster can be used to reduce the lag, and a valve positioner can reduce the dead band. These additional devices are shown in figure 7.


0 v




Figure 5: Electra-pneumatic converter The electro-pneumatic converter is again commonly a force balance device and will convert a 4-20 mA input signal to a 20-100 KPa output signal. The output from the I/P converter is fed to the valve actuator to control the position of the valve stem as shown in figure 6.

Figure 7: Volume booster and valve positioner The simulation includes a first order effect for the valve actuator diaphragm chamber, and gland friction on the valve stem. Provision is also made to introduce the effects that would be produced by including a volume booster and a valve positioner. Finally, the selection of the valve is crucial since a valve which is incorrectly matched to the pipe line system can result in a phenomenon known as saturation and loss of control. The simulation provides a choice of two valves and two pipe diameters.

Figure 6: Control valve actuator



The valve actuator is commonly a diaphragm acting against a spring and it can be arranged so that it requires air to open, or air to close the valve, whichever is more compatible with the nature of the process being controlled and with safety considerations in the event of air supply failure.

The flow rate in a pipeline with fittings and a control valve responds as a first order system to changes in valve position (Harriott 1964). For industrial systems the time constants range from about 0.1 to 5 seconds. Naturally, there is no possibility of instability for a simple first order system.

Movement of the valve stem may not correspond to the output signal from the I/P converter for the following reasons:

The transmitter will contain within itself a feedback system (inherent in the force balance system) and, if it is electronic, is approximately a first order system with a time constant in excess of 0.2 seconds. For a pneumatic system, the transmission line will interact and it can respond as a first or second order system, depending on the length of the line.

The large actuator diaphragm chamber can produce a lag or first order effect. Gland friction on the valve stem can cause large dead bands. Process fluid pressure acting on the valve plug can cause an unbalanced force on the valve stem.

A PI controller is used in flow control systems and will produce a first order effect.


D. W. Tyler, A.K. Quibell / Computer simulation in process control

The I/P converter and the valve actuator will also exhibit first order effects. Thus, even if all the other elements are idealised and there are assumed to be no nonlinearities in the system, the complete closed loop system would be described by a fifth order differential equation. Classical methods of stability analysis for linear systems (such as the Root Locus method) indicate that instability can occur for third and higher order systems. For such systems the degree of stability depends on the loop gain. If the loop gain is too large, instability will occur but, if it is too low, the system response will be too sluggish. 3.2

Proportional control in which the output signal from the controller is directly proportional to the error signal. Reset or integral control in which the output signal is proportional to the time integral of the error signal. Pre-act, rate or derivative control in which the output signal is proportional to the derivative of the error signal (or sometimes the process signal). These modes are generally available in the following combinations:

Loop Gain

The loop gain is the product of the gains of all the elements in the loop. If an element is linear, its gain will be constant but, as has already been demonstrated, the orifice plate has a gain which varies with flow. Valves are also generally non-linear elements. The span of the transmitter can also be varied and, as its span is increased, its gain is decreased. Adjustments to the loop gain, however, are invariably made at the controller and this process is known as tuning. 3.3

modes are commonly available in conventional analog controllers:


Tuning is the process of adjusting the controller so that a compromise is achieved between a number of conflicting requirements such as stability, speed or response and accuracy. With a simple proportional controller, only the gain of the controller is adjusted, but more complex controllers provide derivative and integral components in the output and tuning will involve interactive adjustment of three controller terms. At this point it is perhaps appropriate to consider the two controllers to which the simulation can be interfaced. 4.



The Conventional Analog Controller

A conventional analog controller receives the process signal from the transmitter, compares it with a desired or set point signal and, thus, establishes an error signal E. This error signal may then be processed in the controller in a variety of ways, depending on the mode of control to be used. The following


P + I,

P + D,


Most controllers will also include the following: An automatic/manual switch A remote/local switch used to select the source of the set point. A direct/reverse control action switch A scale with process signal and set point pointers 4.2

Adaptive Gain Controller

The availability of microprocessor controllers allows the use of adaptive gain techniques for a wide variety of problems. The Taylor Microscan controller is a particularly versatile instrument. It provides for adaptive gain as a function of five parameters. 4.2.1

Deviation adaptive gain

A piecewise linear relationship can be set up between the gain and the deviation, as shown in figure 8. The base gain, break points and slopes of the segments of the graph can be set up in a few seconds.




-2 t2 Figure 8: Deviation adaptive gain

D. W. Tyler, A. K. Quibell / Computer simularion in process control

A block diagram representation of the controller with deviation adaptive gain is shown in figure 9.


Controller gain



Cireak points

Figure 11: Remote input adaptive gain 4.2.4

lbS”~&Ltsisal Figure 9: Block Diagram for deviation adaptive gain 4.2.2

Process Adaptive Gain

The process or measurement signal from the transmitter can be used to set up a controller gain characteristic, as shown in Figure 12. Again, base gain, break points and slopes can be varied to obtain a desired characteristic.

Output Adaptive Gain Controller gain

Step changes in control gain can be obtained as a function of the output of the controller. By selecting suitable values for the base gain, break points and gain factors, a stepwise gain characteristic can be obtained, as shown in Figure 10.




I \

/ Beak


Controller gain t3ase gain __ ___-____---x GainFactor1 Basegain ---/ _______ ABe.9gain I GainFactor Bred;pDints

Figure 12: Process adaptive gain 4.2.5

Contact Adaptive Gain

With this form of adaptive gain, the closing of a contact switch somewhere in the plant can be made to produce a step change in the controller gain, as shown in Figure 13. When the contact switch closes at time tl, the controller gain changes by a gain factor, and returns to the original gain when the switch opens at time t2.

Figure 10: Output adaptive gain 4.2.3

Controller gain

Remote Input Adaptive Gain

A controller gain characteristic can be set up as a function of an external or remote signal, as shown in Figure 11. Break points, base gain and slopes can again be varied to obtain a desired characteristic. The remote signal input can be connected to the controller output, the deviation signal or the process signal to obtain even more flexibility.

E&e gain t GainFactor‘-t -----l-l





Figure 13: Contact Adaptive Gain 5.


The interface provides the means for an operator to set up a particular system configuration, adjust the load parameters and make appropriate interconnections between a controller, the four pen recorder and various


D. W. Tyler, A. K. Quibell / Computer simulation in process control

monitoring points (or "transmitter signals") in the simulation. A brief description of these three parts of the interface follows.

settings will be different for the other simulations that are available. 5.3


The Patch Panel

The Interface System Configuration

This consists esentially of an eight position switch, together with two button switches and lights. Table 1 shows the settings for one of the flow control experiments.

Parameter (for flow control simulation)


External 4 Extractor Valve Positioner Volume Booster Transmitter noise Transmitter Damping Valve Characteristic Pipe Diameter PIC Valve

A patch panel is provided, as shown in Figure 14. -I


Press button lit 1t A


Yes No Yes * Yes Yes Equal% Large * Yes

No * Yes * No No * No * Linear* Small No *

PwcEss Nm11m LIN-SW1








Table 1: System configuration settings


The parameters listed in Table 1 will be different for the other simulations that are available.


Figure 14: Patch panel 5.2

The Load Change Section

This consists of a five position switch, together with a load potentiometer for setting an analog signal input to the simulation. Table 2 shows the settings for one of the level control experiments.

Inlet Flow


1 fe'dt evaluation

The valve signal jacks are analog input signals to the computer simulation and should be supplied with signals from the controller output jacks. (The output of either controller can be connected to either of the valve signal inputs.)



100 psi tank


or level control simulation)

The transmitter signals 1, 2, 3 and 4 are analog output signals from the computer simulation. They should be patched to the controller process input jacks and/or the 4-pen recorder inputs.

Periodic change






Both the Quick-Scan (conventional analog controller) and Microscan (microprocessor adaptive gain controller) may be placed in either controller positions. Controller position 1 has four additional jacks to accommodate the additional features of the Microscan. 6.


Table 2: Load change settings During the course of the experiment, these settings will be changed so that the effect of various load disturbances can be investigated. As with Table 1, the parameters and

A piping and instrument (P and I) diagram for the complete set up for a flow control experiment is shown in Figure 15.

D. W. Tyler, A. K. Quibell / Computer simulation in process control


ventional analog controller. For these cases, the open loop gain is measured at various conditions and the adaptive gain features of the Microscan are utilised to achieve correct optimum tuning. Results will be presented and discussed at the presentation of the paper.




A brief review will be presented of the level control simulation. 8.1

P & I diagram of level control

A P & I diagram for the level control simulation is shown in Figure 16.





Figure 15: P & I diagram for flow control The enclosed section of this diagram represents the part of the set up that is computer simulated. Parts of the simulation which are enclosed in a dotted rectangle are those parts which can be inserted, changed or deleted via the interface system configuration assembly. Three transmitter analog outputs from the simulation are also shown, two of these being connected to the recorder. Digital and analog load input signals to the simulation are also shown. 7.


The following experiments are carried out on the flow control simulation to study a variety of real world problems: The effect of D.P. transmitter nonlinearity on loop response. The effects of lags and deadbands in the valve actuator system. The effect of random noise in the measurement signal. The interaction of control valves and lines. The interaction of non-linearities around the control loop. Several of these experiments include tuning and, in some cases, this indicates that optimum tuning is not possible with a con-

Figure 16: P & I diagram for level control Provision is made via the interface system configuration assembly to carry out the following:- Increase or decrease the tank capacity (area). - Insert or delete a volume booster - Vary the level transmitter deadband - Vary the level transmitter span (gain) - Change the valve sizing - Change the tank shape from a vertical cylinder to a spherical tank. 9.


A number of level control experiments can be carried out on this level simulation system


D. W. Tyler, A.K. Quibell / Computer simulation in process control

some of which are listed below:Effect of tank size and valve lag on the general loop performance of a level control system. Averaging level control - or tuning for minimum manipulation. Effect of deadband in a loop - the limit cycle. Effect of non-uniform gain elements in the level control loop. Once again, a number of otherwise intractable problems are solved with the aid of the adaptive gain controller. 10.


A Taylor 1010 process control computer was used to run the simulation and this is designed specifically to handle digital and analog input and output signals. Five work stations are handled simultaneously and each can access a different simulation. A process oriented language (POL*3) is used. A similar system is being developed at Chisholm Institute of Technology. Development of this system has been delayed due to lack of funding for appropriate interface cards, but these have now been acquired and it is anticipated that the development will now proceed. 11.


The benefits that this simulation system offers to the educational process are both real and dramatic. A wide variety of simulations of industrial processes and problems can be presented to students with a high degree of realism. This has been a cooperative venture initiated by Taylor Instrument Company with local Institutes of Technology. Taylor Instrument Company employed an undergraduate student from Swinburne to build and install the interface, and invited a senior lecturer from Chisholm Institute of Technology to test the system and prepare course notes. A pilot course run at Taylor Instrument Company using staff and students from Chisholm Institute of Technology was enthusiastically received. ACKNOWLEDGEMENTS We wish to acknowledge the contributions of Mr. .I.Walker, Mr. B. Thomson and Mr. P. Read of Taylor Instrument Company. Mr. Walker

helped to debug the program, Mr. Read built the interface and Mr. Thomson gave valuable assistance with the instrumentation and lecturing in the pilot course. Thanks are also due to E.C.S. Pty. Ltd. for making available the facilities of their CAD200 computer draughting system for the preparation of the diagrams. REFERENCES Tyler, D.W., Process Control Course at Taylor Instrument Company 1980 - Course notes based on course run by parent company in America. Harriott, P., Inc., 1964.

Process Control,

Microscan Reference Manual. Company.


Taylor Instrument

POL *3 - Process Oriented Language System Reference manual. Taylor Instrument Company.