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Controller Commissioning
Practical methods of setting up a controller
Each controller has to be set up individually to match the characteristics of a particular system. Although there are a number of different techniques by which stable and fast control can be achieved, the Ziegler-Nicholls method has proven to be very effective.
The Ziegler-Nicholls method
The Ziegler-Nicholls frequency response method (sometimes called the critical oscillation method) is very effective in establishing controller settings for the actual load. The method uses the controller as an amplifier to reach the point of instability. At this point the whole system is operating in such a way that the temperature is fluctuating around the set point with a constant amplitude, (see Figure 5.5.5). A small increase in gain, or a reduced proportional band, will make the system unstable, and the control valve will start hunting with increasing amplitude.
Conversely, an increased proportional band will make the process more stable and the amplitude will successively be reduced. At the point of instability, the system characteristic is obtained for the actual operating conditions, including the heat exchanger, control valve, actuator, piping, and temperature sensor.
The controller settings can be determined via the Ziegler-Nicholls method by reading the time period (T n), of the temperature cycles; and the actual proportional band setting at the point of instability.
Bumpless transfer
The technical specifications for controllers include many other terms and one that is frequently encountered is 'bumpless transfer'.
Most controllers incorporate a 'Manual' - 'Auto' switch and there can be times when certain control situations require manual control. This makes interruption of the automatic control loop necessary. Without bumpless transfer, the transfer from Auto to Manual and vice versa would mean that the control levels would be lost, unless the manual output were matched to the automatic output.
Bumpless transfer ensures that the outputs - either Manual to Auto or Auto to Manual - match, and it is only necessary to move the switch as appropriate.
Self-tuning controllers
Contemporary microprocessors provide the ability for some functions, which previously required a computer, to be packed into the confined space of a controller. Amongst these, was the ability to 'self-tune'. Controllers that no longer require a commissioning engineer to go through the process of setting the P I D terms have been available for many years. The self-tune controller switches to on/off control for a certain period of time. During this period it analyses the results of its responses, and calculates and sets its own P I D terms.
It used to be the case that the self-tune function could only apply itself during system start-up; once set by the controller, the P I D terms remained constant, regardless of any later changes in the process.
The modern controller can now operate what is termed an adaptive function, which not only sets the required initial P I D terms, but monitors and re-sets these terms if necessary, according to changes in the process during normal running conditions.
Such controllers are readily available and relatively inexpensive. Their use is becoming increasingly widespread, even for relatively unsophisticated control tasks.
The control task done by the operator is called feedback control, because the operator changes the firing rate based on feedback that he gets from the process via the temperature gauge. Feedback control can be done manually as described here, but it is commonly done automatically, as will be explained in the next section.
To relieve our operator from the tedious task of manual control, we should automate the control loop. This is done as follows:
A PID controller controller has a Set Point (SP) that the operator can set to the desired temperature. The Controller’s Output (CO) sets the position of the control valve. And the temperature measurement, called the Process Variable (PV) gives the controller its much-needed feedback. The process variable and controller output is commonly transmitted via 4 – 20mA, 0-10v signals, or via digital commands (modBus, BACnet etc on a Fieldbus.
When everything is up and running, the PID controller compares the process variable to its set point and calculates the difference between the two signals, also called the Error (E).
Then, based on the Error and the PID controller’s tuning constants, the controller calculates an appropriate controller output that opens the control valve to the right position for keeping the temperature at the set point. If the temperature should rise above its set point, the controller will reduce the valve position and vice versa.
Without automatic controllers, all regulation tasks will have to be done manually. For example: To keep constant the temperature of water discharged from an industrial gas-fired heater, an operator will have to watch a temperature gauge and adjust a fuel gas valve accordingly (Figure 1). If the water temperature becomes too high for some reason, the operator has to close the gas valve a bit – just enough to bring the temperature back to the desired value. If the water becomes too cold, he has to open the gas valve.
The operator, valve, process, and temperature gauge forms a control loop. Any change the operator makes to the gas valve affects the temperature which is fed back to the operator, thereby closing the loop.
For example, a thermostat is a simple negative-feedback control: when the temperature (the "process variable" or PV) goes below a set point (SP), the heater is switched on. Another example could be a pressure switch on an air compressor: when the pressure (PV) drops below the threshold (SP), the pump is powered. Refrigerators and vacuum pumps contain similar mechanisms operating in reverse, but still providing negative feedback to correct errors.
Simple on–off feedback control systems like these are cheap and effective. In some cases, like the simple compressor example, they may represent a good design choice.
In most applications of on–off feedback control, some consideration needs to be given to other costs, such as wear and tear of control valves and maybe other start-up costs when power is reapplied each time the PV drops. Therefore, practical on–off control systems are designed to include a deadband, a region around the setpoint value in which no control action occurs. The width of deadband may be adjustable or programmable.
Linear control systems use linear negative feedback to produce a control signal mathematically based on other variables, with a view to maintain the controlled process within an acceptable operating range.
The output from a linear control system into the controlled process may be in the form of a directly variable signal, such as a valve that may be 0 or 100% open or anywhere in between. Sometimes this is not feasible and so, after calculating the current required corrective signal, a linear control system may repeatedly switch an actuator, such as a pump, motor or heater, fully on and then fully off again, regulating the duty cycle using pulse-width modulation.
Sketch linear control on the board
Describe the control logic of:
On / off control
Proportional + Integral control (P+I)
& PID control, (in your responses you should cover the terms
Offset, deadband, setpoints, response, proportional band, process variable, error etc)
Give examples where each would be used in a building services application
Illustrate your descriptions with sketches
No more than a 1.5 pages excluding diagrams
A control system is a device, or set of devices to manage, command, direct or regulate the behavior of other devices or system.
The term "control system" may be applied to the essentially manual controls that allow an operator, for example, to close and open a gas solenoid valve to bunsen burner, perhaps including logic so that it cannot be opened unless ventilation systems are in operation.
An automatic sequential control system may trigger a series of mechanical actuators in the correct sequence to perform a building function. For example various electric and relay’s and actuators may initiate pumps and the the burners of boilers to provide central heating to a building.
In the case of linear feedback systems, a control loop, including sensors, control algorithms and actuators, is arranged in such a fashion as to try to regulate a variable at a setpoint . An example of this may increase the fuel supply to a biomass boiler when a measured temperature drops. PID controllers are common and effective in cases such as this. Control systems that include some sensing of the results they are trying to achieve are making use of feedback and so can, to some extent, adapt to varying circumstances. Open-loop control systems do not make use of feedback, and run only in pre-arranged ways.
Each of the three modes reacts differently to the error. The amount of response produced by each control mode is adjustable by changing the controller’s tuning settings.
While most controllers use controller gain (Kc) as the proportional setting, some controllers use Proportional Band (PB), which is expressed in percent. Table 1 shows the relationship between Kc and PB.
The proportional control mode is in most cases the main driving force in a controller. It changes the controller output in proportion to the error (Figure 3). If the error gets bigger, the control action gets bigger. This makes a lot of sense, since more control action is needed to correct large errors.
The adjustable setting for proportional control is called the Controller Gain (Kc). A higher controller gain will increase the amount of proportional control action for a given error. If the controller gain is set too high the control loop will begin oscillating and become unstable. If the controller gain is set too low, it will not respond adequately to disturbances or set point changes.
The third control mode in a PID controller is derivative. Derivative control is rarely used in controllers. It is not absolutely required, is very sensitive to measurement noise and it makes trial-and-error tuning more difficult. Nevertheless, using the derivative control mode of a controller can make a control loop respond a little faster than with PI control alone.
The derivative control mode produces an output based on the rate of change of the error (Figure 10). Derivative mode is sometimes called Rate. The derivative mode produces more control action if the error changes at a faster rate. If there is no change in the error, the derivative action is zero. The derivative mode has an adjustable setting called Derivative Time (Td). The larger the derivative time setting, the more derivative action is produced. A derivative time setting of zero effectively turns off this mode. If the derivative time is set too long, oscillations will occur and the control loop will run unstable.
Adjusting the controller gain setting actually influences the integral and derivative control modes too. That is why this parameter is called controller gain and not proportional gain.
Proportional controllers are simple to understand and easy to tune. The controller output is simply the output of the proportional control mode, plus a bias. The bias is needed so that the controller can maintain an output (say at 50%) while there is no error (set point = process variable).
Figure 6 shows the effect of a sudden decrease in fuel gas pressure to the process heater described earlier, and the response of a p-only controller. The decrease in fuel-gas pressure reduces the firing rate and the heater outlet temperature decreases. This creates and error to which the controller responds. However, a new balance-point between control action and error is found and the temperature offset is not eliminated by the proportional controller.
The need for manual reset as described above led to the development of automatic reset or the Integral Control Mode, as we know it today. As long as there is an error present (process variable not at set point), the integral control mode will continuously increment or decrement the controller’s output to reduce the error. Given enough time, integral action will drive the controller output far enough to reduce the error to zero.
If the error is large, the integral mode will increment/decrement the controller output fast, if the error is small, the changes will be slower. For a given error, the speed of the integral action is set by the controller’s integral time setting (Ti). A large value of Ti (long integral time) results in a slow integral action, and a small value of Ti (short integral time) results in a fast integral action (Figure 7). If the integral time is set too long, the controller will be sluggish, if it is set too short, the control lop will oscillate and become unstable.
Under proportional-only control, the offset will remain until the operator manually changes the bias on the controller’s output to remove the offset. It is said that the operator manually “Resets” the controller.
The use of proportional control alone has a large drawback – offset. Offset is a sustained error that cannot be eliminated by proportional control alone. For example, let’s consider controlling the water level in the tank in Figure 5 with a proportional-only controller. As long as the flow out of the tank remains constant, the level will remain at its set point.
But, if the operator should increase the flow out of the tank, the tank level will begin to decrease due to the imbalance between inflow and outflow. While the tank level decreases, the error increases and our proportional controller increases the controller output proportional to this error. Consequently, the valve controlling the flow into the tank opens wider and more water flows into the tank.
As the level continues to decrease, the valve continues to open until it gets to a point where the inflow again matches the outflow. At this point the tank level (and error) will remain constant. Because the error remains constant our P-controller will keep its output constant and the control valve will hold its position. The system now remains at balance, but the tank level remains below its set point. This residual sustained error is called Offset.
Most controllers use integral time in minutes as the unit of measure for integral control, but some others use integral time in seconds, integral gain in repeats per minute or repeats per second. Table 2 compares the different integral units of measure.
A PI controller is made up of the sum of the proportional and integral control actions
The integral mode continues to increment the controller’s output to bring the heater outlet temperature back to its set point. Compared to proportional only control, it is clear how Integral control eliminates offset.
Commonly called the PID controller, its controller output is made up of the sum of the proportional, integral, and derivative control actions.
PID control provides more control action sooner than what is possible with P or PI control. This reduces the effect of a disturbance, and shortens the time it takes for the level to return to its set point.
The graph below compares the recovery under P, PI, and PID control of the process heater outlet temperature after a sudden change in fuel gas pressure as described above.
For your system produce:
Page 103 BSRIA AG07 Library of control strategies for heating
3
http://www.smartdraw.com/downloads/
Your controls system description should describe in words the method of control
Simplified schematics should show the design intent without too much detail. eg. Show all equipment, components and control valves, but no need to show isolation valves, flowrates, or pipe sizes unless this is neccessary to understand the design concept
Your Control logic diagram should clear set out the decision making process of your control system.
Start by identifying your inputs and actions necessary to control your system.
Then think about the decisions that need to be made and possible outcomes
Suggest you sketch out in pencil, I always find this takes several attempts!
Agree with each student the building services control system that they will design.
Some suggestions:
https://www.dropbox.com/s/vzmzkoxd3o5kjcl/Local%20fan%20control%20flow%20chart.docx
Head end computer
In a table schedule, the number, type, manufacturer, size & performance characteristics for a component in the system given to you
Head end computer & Monitor
3 temperature sensors
1x Weather station (temp, wind direction, rain sensor)
1x 16 port Local controller
1x Actuator
1x Speed controller
1x 3 setting User control switch
1x Sub-meter
2x Control Valve
1x DPS
Include a statement saying that the central plant and the field controllers, sensors, etc (not associated with your system) has been covered by others in the group.
Your Specification should include:
Refer to
BSRIA AG09
BSRIA TN10
But make sure you make it project specific.... Refer to WAG as an example.
https://www.dropbox.com/s/01k23mrq8p6bxqy/WAG%20Controls%20Spec.docx
For your system produce:
Task P3.4 moved to assignment 3
You are a commissioning engineer who has been called to the school because their heating control valves keep failing! Described what is happening with the control system & why you think this is happening.You must make a recommendation to resolve the problem
https://www.dropbox.com/s/lvlobiejjc729ox/EH4.exe
The link below is to a mixing circuit. reselect the one or more of the parameters. Press play and write a short paragraph (no more than 200 words) describing the controls of the mixing circuit and commenting on the systems ability to maintain the environmental condition and any consequences to FM
https://www.dropbox.com/s/uh549g3b7cdcmta/EH5.exe
Now change these settings and press play
Before you press play write a short paragraph (no more than 200 words) describing the controls of the throttling circuit
Instability caused by increasing the controller gain, with no 'I' or 'D' action
The procedure for selecting the settings for PID parameters, using the Ziegler-Nicholls method, is as follows:
1.Remove integral action on the controller by increasing the integral time (T i) to its maximum.
2.Remove the controller's derivative action by setting the derivation time (T D) to 0.
3.Wait until the process reaches a stable condition.
4.Reduce the proportional band (increase gain) until the instability point is reached.
5.Measure the time for one period (T n) and register the actual P-band (proportional band) setting on the controller at this point.
6.Using this setting as the start point, calculate the appropriate controller settings according to the values in Figure 5.5.6.
The controller settings may be adjusted further to increase stability or response. The impact of changing the setting of the PID parameters on stability, and the response of the control, is shown in Figure 5.5.7.
Refer to CIBSE Commissioning Code - Automatic Controls section C7 produce a similar schedule for your system.
No more than 1 page of descriptive text + supported by tables, commissioning check lists, and flow charts.