1. INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
& TECHNOLOGY (IJEET)
ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online) IJEET
Volume 4, Issue 2, March – April (2013), pp. 65-70
© IAEME: www.iaeme.com/ijeet.asp
Journal Impact Factor (2013): 5.5028 (Calculated by GISI)
©IAEME
www.jifactor.com
IMPLEMENTATION OF FUZZY LOGIC USING MEMS
ACCELEROMETER FOR CONTROLLING BLDC MOTOR SPEED
1 2 3
R. Devasaran , Pankaj Roy , Dr.Arvind kumar singh
1
Professor, Dept of E&EE, G.N.D. Engg.College, BIDAR, Karnataka, India
2
Professor and HOD. Dept of E&EE, BIT, Sindri, Bihara, India
3
Associate Professor, NERIST, Arunachal Pradesh, India
ABSTRACT
A fuzzy logic controller (FLC) is a flexible mathematical structure which is capable
of identifying complex nonlinear relationships between input and output data sets. In this
project a three dimensional accelerometer sensor is used as input devices for the system. The
output of this accelerometer sensor is analog in nature, to digitize these signals and to
transmit over wireless medium we are using arduino based ATmega8 micro controller. ISM
band RF modules are used to communicate over wireless medium. The MSP430 is a mixed-
signal microcontroller family from Texas Instruments. Built around a 16-bit CPU, the
MSP430 is designed for low cost and, specifically, low power consumption embedded
applications. This micro controller is used at the receiver end to receive data and control the
motor speed depending on the received data from fuzzy table.
Keywords: Fuzzy logic Arduino, MSP430, Accelerometer.
I. INTRODUCTION
Fuzzy logic is the theory of fuzzy sets, sets that calibrate vagueness. Fuzzy logic is
based on the idea that all things admit of degrees. Temperature, height, speed, distance,
beauty – all comes on a sliding scale. Many decision-making and problem-solving tasks are
too complex to be understood quantitatively, however, people succeed by using knowledge
that is imprecise rather than precise. Fuzzy set theory resembles human reasoning in its use of
approximate information and uncertainty to generate decisions. It was specifically designed
to mathematically represent uncertainty and vagueness and provide formalized tools for
dealing with the imprecision intrinsic to many engineering and decision problems in a more
65

2. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
natural way. Speed control of BLDC motors has been one of the crucial topics in
mechatronics engineering. Starting from simple Cartesian robots, to giant industries such as
steel where maintaining motor speed of rollers bars. Due to non linearity of BLDC motors,
designing control system based on system identification is difficult and al system parameters
are approximated. Fuzzy logic controllers can be practically implemented using several
techniques using microcontroller where all fuzzy rules are placed by means of assembly
language or fl chip that is configurable using accompanying software and finally using pc
where education mainly takes place in development process.
Fig.1. Fuzzy logic levels
II. SYSTEM ARCHITECTURE
In this system we have two units, transmitter unit and receiver unit. In the transmitter
unit we are using accelerometer as input devices.
Fig.2. DC Motor speed control block diagram
66

3. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
The output of accelerometer is analog in nature, to convert these analog signals into
digital form we are using in-built six channel ADC of Atmega8 micro controller. By using
fuzzy logic table we are comparing present input readings with already observed pre-defined
input readings. For matched readings we will transmit four digital data bits through RF
transmitter.
Fig.3. Transmitter unit
In the receiver unit RF receiver will receive four data bits from transmitter and depending on
the received data bits motor speed will be controlled. For this purpose we are using MSP430
controller. But micro controller cannot control motor directly in between it needs a driver
circuit. L293D IC is used as driver circuitry.
Fig.4. Receiver circuit
67

4. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
Fuzzy table:
X Y Z RESULT DUTY CYCLE
200-300 50-220 150-280 0011 0%
50-200 350-640 80-150 1001 25%
300-580 220-350 280-580 1010 50%
580-900 640-890 580-890 1011 75%
900-1020 890-1015 899-1010 1110 100%
III. ACCELEROMETER GESTURE RECOGNITION
Accelerometer sensor is used for gesture recognition. An accelerometer is a device
that measures the vibration, or acceleration of motion and produces different voltage levels.
The force caused by vibration or a change in motion (acceleration) causes the mass which
produces an electrical charge that is proportional to the force exerted upon it. Since the
charge is proportional to the force, and the mass is a constant, then the charge is also
proportional to the acceleration.
Fig.5. Flow chart for gesture recognition
68

5. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
In this project we are using ADXL335 accelerometer which is a 3-dimensional
accelerometer. This board measures acceleration in three dimensions(X, Y&Z) and produces
three different voltage levels. The output of accelerometer is analog in nature, to convert
these analog signals into digital form, we are using in-built ADC of Atmega8 micro
controller.
Here, Atmega8 micro controllers continuously read data from accelerometer and
convert them into digital form. This digitized data is compared with the data which is already
taken in the accelerometer analysis part. And for every movement of accelerometer four data
bits are assigned. Now, in the comparison phase digitized data is compared with the pre-
defined ranges, and for matched range corresponding data bits will be transmitted through
ISM band RF transmitter.
VI. EXPERIMENTAL RESULTS
We have successfully implemented the project tested for different duty cycles with
input device as accelerometer and touch screen. when the accelerometer is in forward
direction duty cycle is 100%, when it is in right direction duty cycle is 75%, when it is in left
direction duty cycle is 50%, and when it is in back direction duty cycle is 25%. Similarly
when the select switch is LOW touch screen is selected, when we touch in 1st quadrant motor
runs with 100% duty cycle, when we touch in 2nd quadrant motor runs with 75% duty cycle,
when we touch in 3rd quadrant motor runs with 50% duty cycle, and when 4th quadrant is
pressed motor runs with 25% duty cycle.
Fig.6. Motor Action
V. CONCLUSION AND FUTURE SCOPE
A fuzzy logic controller using MEMS accelerometer has been implemented that gives
excellent performance in terms of duty cycle. The results of experiment on the real plant
demonstrate that the proposed fuzzy logic controller is able to sensitiveness to variation of the
reference speed attention. The results of the control are as follows. The speed control of bldc
motor showed the proposed controller gains optimal performance. The proposed controller
achieved to overcome the disadvantage of the use conventional control sensitiveness to
inertia variation and sensitiveness to variation of the speed with drive system of bldc motor.
69

6. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
REFERENCES
[1]. NEURO-FUZZY AND SOFT COMPUTING -Jyh-shing Roger Jang, Chuen-Tsai
Sun*3+ P. K. Nandam, and P. C. Sen,
[2]. Yodyium Tipsuwan and Mo-Yuen Chow, “Fuzzy Logic microcontroller
implementation for DC motor speed control”, IEEE Transactions on Power
Electronics, V0l.11, No.3, June 1999, pp 1271-1276.
[3]. “Fuzzy remote controller for converter DC motor drives”, Paritantra, Vol. 9, No. 1,
June 2004.
[4]. “Remote fuzzy logic control system For a DC motor speed control”, Journal Teknik
Elektro Vol. 2, No. 1, Maret 2002: 8 – 12
[5]. S. Yuvarajan, Abdollah Khoei and Kh. Hadidi, “Fuzzy logic DC motor controller with
improved performance”, IEEE Transactions on Power Electronics, Vol. 11, No.3,
August 1998, pp 1652-1656.
[6]. F.I. Ahmed, A.M. El-Tobshy, A. A. Mahfouz, and M. M. Ibrahim, “(I-P) Adaptive
controller for dc motor drives: a hardware and software approach”, Conference
Publication No. 455,
[7]. Gilbert0 C.D. Sousa, and Bimal K. Bose, January/ February 1994, “A fuzzy set theory
based control of a phase-controlled converter dc machine drive“, IEEE Trans.
Industry Applications, 30, no. 1, 34-43.
[8]. J. Holtz “Pulse width modulation for electric power conversion”, Proc.IEEE, vol.82,
pp.1194-1214, Aug. 1994.
[9]. M.Gowrisankar and Dr. A. Nirmalkumar, “Implementation & Simulation of Fuzzy
Logic Controllers for the Speed Control of Induction Motor and Performance
Evaluation of Certain Membership Functions” International Journal of Electrical
Engineering & Technology (IJEET), Volume 2, Issue 1, 2011, pp. 25 - 35,
ISSN Print : 0976-6545, ISSN Online: 0976-6553.
[10]. Vilas S Bugade and Dr. Y. P. Nerkar, “Comparison of Brushless D. C. (BLDC) and
Printed Circuit D. C. Motors for the Electric Bicycle Application” International
Journal of Electrical Engineering & Technology (IJEET), Volume 1, Issue 1, 2010,
pp. 144 - 156, ISSN Print : 0976-6545, ISSN Online: 0976-6553.
[11]. VenkataRamesh.Edara, B.Amarendra Reddy, Srikanth Monangi and M.Vimala,
“Analytical Structures for Fuzzy Pid Controllers and Applications” International
Journal of Electrical Engineering & Technology (IJEET), Volume 1, Issue 1, 2010,
pp. 1 - 17, ISSN Print: 0976-6545, ISSN Online: 0976-6553.
70