Journal of Software Engineering and Applications, 2011, 4, 161-171
doi:10.4236/jsea.2011.43018 Published Online March 2011 (
Copyright © 2011 SciRes. JSEA
A Design of a PID Self-Tuning Controller Using
Mohammad A. K. Alia, Tariq M. Younes, Shebel A. Alsabbah
Mechatroncis Engineering Department, Faculty of Engineering Technology, Al-Balqa Applied University, Amman, Jordan.
Received February 20th, 2011; revised March 5th, 2011; accepted M ar c h 9 th, 2011.
In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses
an open –loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates control-
ler parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as
a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to
control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of con-
troller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or
self-tuning mo de.
Keywords: PID Control, Manual Tuning, Self-Tuning, Open-Loop Relay Test, Process Variable, System Offset Error
1. Introduction
Proportional integral derivative (PID) control method
(algorithm) has been the most popular control method,
which is widely used in control engineering. From an au-
tomation perspective, PID is more than enough for 99%
of control situations. It is well known that a great many
systems have very simple dynamics and in these situa-
tions PID is often sufficient to provide the performance
needed. Many industrial control loops that are nonlinear
to some degree are linear enough in the control region
near the set point for which PID co ntrol algorithm works
fine. PID controllers can be more intuitive to tune. For
example it is easier to reason out the expected behavior
while changing one of the PID gains than pole placement
option. There are many advantages of PID’s such as their
simplicity and possibility of coupling PID algorith m with
smith predicator, feed-forward loops, nonlinear gain sch-
eduling and other advanced control techniques [1,2].
PID controllers have some drawbacks that limit their
effectiveness. One of the current difficulties with PID
controllers is the gain tuning. Although there are auto-
tuning algorithms available yet an experienced engineer
is still required to fine tune the co ntroller and ensure sys-
tem stability. In the majority of cases PID tuning invol-
ves trial, (and) error and direct intervention o f the opera-
tor during the tuning process particularly during distur-
bance tuning when it is not always obvious whether the
process variable is reacting to the control effort or to ad-
ditional disturbances or measurement noise [3-5]. An-
other drawback of PID controllers is that process dyna-
mics might change over time. This can happen due to va-
riation of (changes of) the process load, and normal wear
and tear. To compensate for process behavior change o ver
time, expert users are requ ired to recalibrate the PID gain s.
This drives up costs for labor and down time. In order to
eliminate the need for operator intervention, it is recom-
mended that control tuning be enabled when the process
variable begins a limit cycle [6,7], which may be detected
easily, also it contains enough information for determin-
ing a new set of controller parameters. This is what we
are going to do .
2. Basic Idea and Design Considerations
The target of this work is to design a LabVIEW–based
self-tuning PID controller and to verify its performance
using a process flow-rate trainer which exists at the la-
boratory of process control. For this purpose an ISA
standard form of PID algorithm was designed. In order to
eliminate the effect of external noise on measurement, a
low pass fifth order filter (FIR) is used. For controller to
react on the controlled system error only, and to avoid
flattering, the controller initiates the tuning process only
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
after the existence of an error for a predetermined time
interval. In order to realize the required time delay a spe-
cific ON- delay timer was designed in compliance with
the concept of data flow programming [8]. The On-delay
timer is illustrated in Figure 1.
The range of set point is (0-2) V while the controller
output range is (0-10) VS. In order to avoid problems
associated with closed-loop tuning [4-5], the controller
applies an open-loop set point relay test by forcing the
process variable into a series of sustained oscillations
known as a limit cycle. The operator has the choice to se-
lect the appropriate number of oscillations. In order to
obtain more tuning accuracy it is preferred to increase the
number of oscillations and take the average (TU). Once
the parameter settings have been loaded into the PID for-
mula, the controller is returned to the automatic mode . In
this connection we should refer to the basic difference
between the designed self-tuning controller and the auto-
tuning controller toolkit of LabVIEW [9]. We do not use
a wizard and human intervention is excluded more over
we apply an automatic open-loop tuning procedure inst-
ead of closed-loop tuning.
3. PID Self-Tuning VI Flowchart
Figure 2 shows the flow chart. When the VI runs it reads
the data from the analog input and filters the process va-
riable. If the auto-tuning is activated by the auto-tuning
pushbutton or as a result of disturbance, the controller
switches to the open-loop mode.
When the system is in steady state the tuning process
starts. When a limit cycle exists with the required num-
ber of cycles, new PID parameters are evaluated, then
PID controller parameters are updated and the auto-tuning
process is stopped. If the stop pushbutton is not pressed
the controller goes to next iteration, else it sends a zero
output and stops. When the auto-tuning is off, the con-
troller works as a normal PID controller, then it adds the
required bias to its value and coerces it in range if the
stop pushbutton is not pressed.
4. Description of Self-Tuning PID Controller
4.1. The Front Panel
The front panel is shown in Figure 3. It includes the fol-
lowing controls and indicators.
Kp: the value of the proportiona l controller gain.
Ki: the value of the integral gain.
Kd: the value of the derivative gain Kd.
SP: desired steady state value.
Bias: the value added to controller output and when
the error equals zero the ou tput equal the bias value.
SS Ripple band: the accepted va lue of ripple for process
variable in order to consider that steady state occurred.
Relay Amplitude: the value of Sp relay.
# of Cycles: the number of cycles that must occur to
stop tuning.
Mode: a select switch between automatic and manual
Manual Control: the value to send at manual mode.
Manual: makes automatic to manual modes change.
Auto Tuning: starts auto-tuning operation.
Stop: the abort push button.
PV: the current value of process variable.
Error: the value of subtracting current PV from SP.
Out: the value of current controller output in volt.
4.2. The Block Diagram
The block diagram is shown in Figure 4. It includes the
PID auto-tuning (all features) SubVI, Filtering and smoo-
thing wave form SubVI, and the waveform values aver-
age SubVI.
The hierarchy of the VI is shown in F igure 5.
The PID auto-tuning (all features) SubVI is shown in
Figure 6. It includes the following SubVIs:
4.2.1. Restart Response VI
It sends zero volt as a controller output when it is enabled.
When the process variable (PV) becomes zero the pro-
cess starts again. The block diagram is given in Figure 7.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 1. On-delay timer block diagram.
Figure 2. PID auto-tuning VI flow chart.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 3. The front panel of PID auto-tuning VI.
Figure 4. PID auto-tuning VI block diagram.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 5. PID auto-tuning VI hierarchy.
Figure 6. PID auto-tuning (all features) block diagram.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
4.2.2. Ste ady State Test SubVI
It indicates when the (PV) is at steady state. The block
diagram is shown in Figure 8.
4.2.3. Calculate Best PID Parameters VI
The block diagram is given in Figure 9.
4.2.4. Check Oscillation SubVI
It indicates if the (PV) is in an oscillatory mode.
The block diagram is shown in Figure 10.
4.2.5. Find Iteration Time SubVI
It calculates the time interval between every two itera-
tions. The block diagram is shown in Figure 11.
4.2.6. SetPoint Relay Test SubVI
If PV < (SP 0. 5 dea d band), then (SP = SP + relay am-
plitude) else if PV < (SP + 0.5 dead band), then (SP = SP
—relay amplitude). The block diagram is shown in Fig-
ure 12.
4.2.7. PID Controller SubVI
It performs the standard PID algorithm. The block dia-
gram is illustrated in Figure 13.
This SubVI includes:
Calculate Error SubVI
Integral term SubVI
Derivative term SubVI
Figure 7. Restart response block diagram.
Figure 8. SS test block diagram.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 9. Calculate best PID parameters block diagram.
Figure 10. Check oscillation block diagram.
Figure 11. Find iteration time (dt) block diagram.
4.2.8. Stop W atch SubVI
The block diagram is illustrated in Figure 14.
4.3. Filtering and Smoothing SubVI
The VI performs double filtering for the read samples in
one iteration (acquisition). Firstly it performs an averag-
ing to improve the measurement, then u ses (FIR) filter in
order to eliminate noise effect on samples. The block dia-
gram is shown in Figure 15.
4.3.1. Waveform for Value s Average SubVI
The block diagram is given in Figure 16.
5. Experimental Procedure and
Experimental Results
Initially, the designed PID self-tuned controller was in-
stalled. The hardware DAQ-board (PCI-MIO-16E-1) was
also installed an d the required inp ut/output are co nfigured.
The feedback signal and the DAQ-board output were
connected to a flow controller process trainer [10-11].
GUI software was designed and used to select the control
mode, PID gain values. GUI allows the operator to run
manual or self-tuning modes of operation.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 12. SP relay bloc k diagr a m.
Figure 13. PID controller block diagram.
Figure 14. Stop watch bloc k diagr a m.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 15. Filtering & smoothing waveform block diagram.
5.1. Proportional Control Mode
Initially the process is kept ru nning in a proportio nal mo-
de until it reaches a steady state. The user pushes the auto-
tuning pushbutton which triggers the tuning process. The
system switches to an open-loop mode. When it exists in
a steady state the relay test starts. When the process vari-
able oscillations are steady, the gain is calculated and
then the controller gain is updated, and the process is run
in a closed-loop mode.
Figure 17 illustrates the tuning steps when :
Set point = 4.00 V, Kp = 1.39, relay voltage 1.00 V and
the number of oscillations = 4.
Figure 16. Waveform values average block diagram.
Figure 17. A graph indicator for a P mode.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 18. A graph indicator for P mode.
Figure 19. A graph indicator for PI mode.
A Design of a PID Self-Tuning Controller Using LabVIEW
Copyright © 2011 SciRes. JSEA
Figure 20. A graph indicator for PID mode.
Figure 18 shows a self-tuning process, when the sys-
tem was subjected to a disturbance from the load side.
The tuned gain value was found (Kp = 1.42).
5.2. PI and PID Control Modes
Tuning steps are the same as in proportional contro l mo-
de. Figure 19 shows the tuning for a PI controller when
Set point = 4.00 V, Kp = 1.09, KI = 0.67.
Figure 20 shows the tuning process of a PID control-
ler when: Setpoint = 4.00 V, Kp = 1.77, KI = 0.83 and Kd
= 0.19.
6. Conclusions
Using LabVIEW software a self-tuning PID controller
was designed and tested to control the water flow rate.
The designed controller may be considered as a devel-
opment to auto-tuning toolkit of labVIEW.
The controller includes a standard PID controller with
the required SubVIs which enables an open-loop self-
tuning process without operator intervention. A manual
tuning option is also av ailable.
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