6545(Print), ISSN (Online) Volume 4, Issue 2, March April (2013), IAEME & TECHNOLOGY (IJEET)

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1 INTERNATIONAL International Journal of JOURNAL Electrical Engineering OF ELECTRICAL and Technology (IJEET), ENGINEERING ISSN 0976 & TECHNOLOGY (IJEET) ISSN (Print) ISSN (Online) Volume 4, Issue 2, March April (2013), pp IAEME: Journal Impact Factor (2013): (Calculated by GISI) IJEET I A E M E IMPLEMENTATION OF FUZZY LOGIC USING MEMS ACCELEROMETER FOR CONTROLLING BLDC MOTOR SPEED R. Devasaran 1, Pankaj Roy 2, Dr.Arvind kumar singh 3 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 mixedsignal 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 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 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 Fuzzy table: X Y Z RESULT DUTY CYCLE % % % % % 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 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 predefined 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 1 st quadrant motor runs with 100% duty cycle, when we touch in 2 nd quadrant motor runs with 75% duty cycle, when we touch in 3 rd quadrant motor runs with 50% duty cycle, and when 4 th quadrant is pressed motor runs with 25% duty cycle. V. CONCLUSION AND FUTURE SCOPE Fig.6. Motor Action 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 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 [3]. Fuzzy remote controller for converter DC motor drives, Paritantra, Vol. 9, No. 1, June [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 [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, [8]. J. Holtz Pulse width modulation for electric power conversion, Proc.IEEE, vol.82, pp , Aug [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 , ISSN Print : , ISSN Online: [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 , ISSN Print : , ISSN Online: [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: , ISSN Online: