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LabVIEW Based PID Speed Control and System

Identification of a PMDC MotorKiran Raj A S

*, Manoj Kumar T, Mansi S Surana, Prem Kumar M P, Suchithra R , Varun K

Department of Electronics and Instrumentation, Amrita Vishwa Vidhyapeetam

Amrita School of Engineering, Coimbatore, India

*anilkiran.191@gmail.com

Abstract-Speed control of DC Motor is vital in manyapplications. In this paper, we are trying to control the speed of

the PMDC motor and finding the model of the closed loop

system. The objective is achieved in two steps. First, we interface

the PMDC motor to PC using NI USB-6008 DAQ card. For

designing the PID controller, LabVIEW control system toolkit is

used. Next, we extract the state-space model of the closed loop

speed control system using LabVIEW System Identification

Toolkit. The state-space model derived from this system can beused in the model based fault detection technique for finding out

the faults which could occur in the system or for model based

controls.

Key words: DC motor, PID, USB-6008, LabVIEW,

System identification, State-space.

I. INTRODUCTIONDC Motor plays a crucial role in research and laboratory

experiments because of their simplicity and low cost. The

basic property of DC motor is that speed can by adjusted byvarying the terminal voltage. In order to adjust the speed of

the system Proportional Integral Derivative (PID) controller is

widely used [1], [2]. This method is most useful when a

mathematical model of the process or control is too

complicated or unknown. Tuning of PID parameters should be

done to get the optimal response. Many times when workingwith DC motors, specifications of the motor remains

unknown, and hence it is imperative to go for system

identification to obtain the model. The motor used for closed

loop speed control and system identification is manufactured

by canon precision motors with voltage rating of 12V and

rated RPM of 2200.

II. THEORYA. PID Controller And Tuning Algorithm:The PID controller which consists of proportional integral

derivative elements is widely used in feedback control of

industrial processes. It takes action on considering the past

present and future errors. By tuning the three parameters (Kp,

Ki , Kd) in the PID controller algorithm [3], thecontroller canprovide control action designed for specific process

requirements.

The relation between controller output and error input in PID

controller is given by:

y(t)= Kpe(t)+ KpKi + KpKd

where,

Ki= and Kd=

PID controllers are tuned in terms of their P, I, and D terms.

There are two ways of tuning they are

1) Ziegler Nichols method (Closed-loop): Ziegler-Nichols [4] is a type of continuous cycling method forcontroller tuning. The term continuous cycling refers

to a continuous oscillation with constant amplitude

and is based on the trial-and-error procedure of

changing the proportional gain (Kp). The kp is reduced

from larger value till the point at which the system

goes to unstable state i.e. the point at which thecontinuous oscillations occurs. Thus the gain at which

system starts oscillating is noted as ultimate gain (Ku)

and period of oscillations is ultimate time period (Pu).

It allows us to use the ultimate gain value, Ku, and theultimate period of oscillation, Pu, to calculateKc.

These two parameters,KuandPu, are used to find the

loop-tuning constants of the controller (P, PI, or PID)

using the formula tabulated in Table 1.

Table IPID Controller Parameters for Ziegler-Nichols Method

The advantage of this method is that it is a proven

online method and includes dynamics of whole

process, which gives a more accurate picture of how

the system is behaving. The disadvantage is that it

upsets the process, uses trial and errormethod and has

Controller type Kp Ti Td

P 0.5Ku 0

PI 0.45Ku Pu/1.2 0

PID 0.6Ku Pu/2 Pu/8

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a very aggressive tuning. This closed-loop tuning

method is limited to tuningprocesses that cannot runin an open-loop environment.

2) Process reaction curve (Open-loop): In the processreaction curve, the variables being measured are those

of a system that is already in place. A disturbance is

introduced into the system and data can then beobtained from this curve. First the system is allowed

to reach steady state, and then a disturbance,Xo, is

introduced to it. The percentage of disturbance to the

system can be introduced by a change in either the set

point or process variableFrom the data logged the three parameters are

calculated by using the process reaction curve for a

step change in input for open loop system. The dead

time (dead), the time for response to change () and the

ultimate value the response reaches at steady state

(Mu) for a step change of xo.

Ko=

This Koand deadare used to find the tuning constants

by using the formula Table 2.

Table II

PID Controller Parameters for Process Reaction Curve Method

Controller

Type

Kc Ti Td

P Ko 0

PI 0.9Ko 3.3dead 0

PID 1.2Ko 2dead 0.5dead

The advantage of this method is that quick and easier

to use than other methods and it is a robust and

popular method and the disadvantages are it depends

upon purely proportional measurement to estimate I

and D controllers and approximations for the Kc, Ti,

and Tdvalues might not be entirely accurate for

different systems.

So on analysing both the methods, we decided to use

Ziegler Nichols method (Closed-loop), since it is

very accurate and works on the dynamic data of the

system.

The PID parameters we got are as follows:

Kp=0.00038

Ti=0.0026 s

Td=0.01 s

B. System IdentificationIn order to obtain a well defined model, a numerical process

known as system identification is used. This process involves

acquiring data from a plant and then numerically analyzing

stimulus and response data to estimate the parameters of the

plant.

System identification is a process that includes acquiring,

formatting, processing, and identifying mathematical modelsbased on raw data from a real-world system. Then the result is

validated such that the resulting model fits the observed

system behaviour. System identification is used in a wide

range of applications including mechanical engineering,biology, physiology, meteorology, economics, and model-

based control design.

The identification of models in closed loop systems can be

done in three ways. They are direct identification, indirect

identification and joint input-output approach.

Direct identification is used when onlyknowledge about the stimulus and response

signal is present. This can be used for SISO,

MISO and MIMO systems.

Indirect identification approach is used whenknowledge about the response signal, referencesignal and controller information is present.

Joint identification approach is used when theknowledge about stimulus signal, response

signal and reference signal is present.

Both the Indirect and Joint identification can be used only for

SISO systems. In our project, only information on stimulus

and response signal is known hence only direct identificationapproach is used. In this, State space estimation method is

used since it does not assume zero correlation between input

signal and output noise.

III. EXPERIMENTAL SETUPA. Hard Ware1) Optical Switch Arrangement: Moc7811 is a slotted

opto-isolator module with an IR transmitter and a

photo diode mounted on it. When the light emitted by

the transmitter is blocked by the slotted disc, logiclevel of the photo diode changes. The optical switch

for producing pulse for speed measurement is shown

in Fig. 1.

Fig.1 Optical Switch Circuit

2) Frequency To Voltage Converter: LM2907 is afrequency to voltage converter IC which is used for

measuring the speed of the motor. Input to this

converter is given as pulses which are produced from

the optical switch. LM2907 converts the given input

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pulse frequency to a proportional voltage. The circuit

connection for 2907 is shown in Fig. 2.

Fig. 2 Frequency to Voltage Converter Circuit

3) Motor Driver Circuit: The PID controller output isgiven as an analog signal of range 0-5V through the

motor driving circuitry for driving the motor. This

circuit consists of 2 stages.

Voltage amplification Current amplification

First, IC 741 is used to amplify the voltage signal

from DAQ card which in the range of 0-5V to 0-12V

range for meeting the voltage specification of the

motor. Since the output current of the IC 741 is in the

range of milli Amperes, we need to amplify the

current for driving the motor. This amplification isdone by connecting the TIP122 NPN power

transistor in common collector configuration. The

property of the common collector configuration is

that the voltage gain is unity and the current gain is

equal to the maximum current gain of the transistor.

Therefore, the current amplified output is given tothe motor from the emitter junction of the TIP122.

By this way, the motor can be driven properly and

circuit connection is made as shown in Fig. 3.

Fig. 3 Voltage and Current Amplification Circuit

B. SoftwareA LabVIEW platform is used to interface the PID controller

with the DC motor for controlling the speed of the motor

through NIDAQ card USB-6008 [5]. The main advantage of

LabVIEW is that it offers a variety of toolkits for controlpurposes so that the entire steps of the design process from

system identification to simulation verification can be done on

the same platform.

1) Closed Loop PID Speed Control: The desired speed isobtained from the user and the actual speed of the motor

is received through the DAQ card from the speed

measurement circuitry. The desired speed, the actualspeed and the PID gains calculated from the ultimate

gain method [6] are given as inputs to the PID

controller which in turn produces the controller output

in the range of 0-5V through the DAQ card. The set up

for controlling the speed of the motor is done as shown

in functional block diagram of closed loop system in

Fig. 4.

Fig. 4 Functional Block Diagram of Closed Loop Speed Control System ofDc Motor

The LabVIEW block diagram of closed loop speed

control system is shown in Fig 5 and hardware setup

and result is shown in Fig.6 and Fig. 7 respectively.

Fig. 5 LabVIEW Block Diagram of Closed Loop Speed Control System

Fig. 6 Hardware Setup

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REFERENCES

[1] R.Isermann, Fault-diagnosis systems - An introduction from Fault

Detectionto Fault Tolerance,New York: Springer-Verlag, 2006, pp. 369-390.

[2] Guoshing Huang and Shuocheng Lee, PC-based PID speed control in DC

motor, Audio, Language and Image Processing, 2008.ICALIP 2008.

International Conference on, 2008, pp.400407.

[3]LabVIEW PID Control Toolset User Manual, National Instruments, 2001.

[4] Curtis D. Johnson, Process control instrumentation technology,Prentice-Hall,2006

[5] LabVIEW DAQ USB-6008/6009 User Manual, National Instruments,

2008.

[6]George Stephanopolous, Chemical process control- An Introduction toTheory and Practise, New Delhi: Prentice-Hall, 2009, pp.258-279,352-355.

[7] LabVIEW System Identification Toolkit User Manual, National

Instruments,2006.