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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.

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Fz3310671070

  1. 1. Utsav modi, Parita patel / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.1067-10701067 | P a g eControlling Temperature of water Using Microcontroller AndCorrection Using Fuzzy LogicUtsav modi, Parita patelAbstractMany people of our country is involvein fishery, but different fish live in differenttemperature and pressure if the temperaturevary the fish may be die, so the temperaturemust maintain within certain range but it is verydifficult for them to maintain the temperatureand pressure, if they try to maintain all theparameter the cost also higher, so we must thinka alternate process which is our desire project.In this project we basically control thewater temperature using microcontrollerPIC18F4520.We first measure the watertemperature of the water and then display it inthe seven segment display now if thetemperature is higher than on the cooler and ifthe temperature is lower than on the hot air fan.We also use fuzzy controller to control the watertemperature and pressure perfectly.To program the microcontroller wefirst write the program in C-language, and thenwe convert the code in the hexadecimal code andburn the code within the chip and configure themicrocontroller according to our requirementand perform all operation.Keywords—Fuzzy Logic, Microcontroller,PIC18F4520, RS232, Lampex DisplayI. INTRODUCTIONWith the help of this project we contributein our society and help many people who involve inthe fishery. They get benefited from this projectand their cost for business gets reduced so they getmore profit. So this project is very much beneficialfor our society as well as for our country. Oursociety gets benefit from this project and we canmaintain all the parameter perfectly, the cost ofmaintain the temperature of the water get reducedand all can be done automatically without any manpower, so it is very social project. The project isalmost run perfectly but to control the temperaturewe must use fuzzy logic as well as fuzzy chip, buttill d fuzzy chip is not available in our country andthe cost is very much high, this is the main problemwith this project.II. DETAIL OF THE RESEARCH WORKIn this project control the temperature ofwater according to the necessity of the living of thefish. I.e. different fishsurvive in differenttemperature and pressure so we must maintain theproper temperature and pressure of the water. Herewe first measure the temperature of the water byusing a thermocouple if the temperature is highthen we start the cooler system and if thetemperature is low we on the hot water system, soby this method we maintain the proper temperatureof the water. We also use fuzzy logic system tomaintain the system within a proper range oftemperature. We control the water temperature byusing microcontroller pic18f4520 (pic seriesmicrocontroller) this microcontroller has 10 bitADC converter which is able to sense temperatureand display it in the lampex display, first weprepare the aquarium and place a thermocouple inthe water, now the temperature converted to thevoltage with the help of this thermocouple andconverted to the digital format with the help of thismicrocontroller. Now if the measured temperatureis out of range (the range which the fish cantolerate) we on our cooling system (which is ac fanor general cold water flow system),and the watertemperature is cooling down towards normal rangeand we compare the temperature with the standardtemperature if now this temperature is equal to thethreshold and we leave the system without anychange, now if the temperature is cold then we onthe hot air system and water temperature is raisedtowards higher order and compare the temperatureof threshold and if the temperature is equal to thethreshold then we are not interested for any kind ofchange. We run the system after a certain intervalof time within 24 hours, and fish can survive withinthe temperature without any problem. Now tocontrol the temperature we apply fuzzy chipcontroller which check the temperature from theinput and decide within which range it fall (I.e. hot,cold, very hot, very cold, normal etc)and fuzzified(fuzzification can be done by OR,AND ,NOTlogic) the temperature and process the temperatureto control it, and after processing it againdefuzzified(by max membership principle, centroidmethod, weighted average method or mean maxmembership method) and send it to the output ofthe controller.Fuzzy logic deals with the uncertainty inengineering by attaching degree of certainty to theanswer to a logical question. It is commercial andpractical. Commercially, fuzzy logic has been usedwith great success to control machines andconsumer products. In the right applications fuzzy
  2. 2. Utsav modi, Parita patel / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.1067-10701068 | P a g elogic systems are simple to design, and can beunderstood and implemented by non-specialist incontrol theory. In most cases someone with aintermediate technical background can design afuzzy logic controller. The control system will notbe optimal but it can be acceptable. Controlengineers also use it in applications where the on-board computing is very limited and adequatecontrol is enough. Fuzzy logic can implement incontrol system where simplicity and speed isimportant. Fuzzy logic can be used in the followingapplications:Environmental control• Air conditions• HumidifiersDomestic Goods• Washing machines/dryers• Vacuum cleaners• Toasters• Microwave ovens• RefrigeratorsConsumer electronics• Television• Photocopiers• Still and video cameras• Hi-fi systemsAutomotive systems• Vehicle climate control• Automatic gearboxes• Four –wheel steering• Seat/mirror control systems• This is a list and gives an idea of the keyapplications areas. In general it explains applicationof fuzzy controller.Engineering motivation• In engineering we can apply fuzzy logicand can solve any problem with the help of thisfuzzy logic rather we can obtain a optimumsolution for any problem. A traditional logicdecision block produces an outcome based uponbinary logic. A firm YES or NO emerges as anoutput of the decision block. However the inventorof fuzzy logic LOFI ZADEH, noted that humandecision making incorporate shades of meaning inwhich binary YES/NO might be replaced by• DEFINITELY YES• PROBABLY YES• MAYBE• PROBABLY NO• DEFINITE NO• Fuzzy logic copies this feature of humandecision making using levels of possibility in anumber of uncertain (or fuzzy) categories .forexample, think about the coupled tank system inwhich the object is to adjust the input voltage, u, tothe to the pump motor (as in fig1) so that level intank 2 is held at a steady state value. The measuredoutput is level in tank 2, denoted by the signal y2.Acommon sense controller could use the followingfuzzy control rules:• IF {LEVEL TOO HIGH} THEN{REDUCE PUMP VOLTAGE}• IF {LEVEL TOO LOW} THEN{INCREASE PUMP VOLTAGE}• IF {LEVEL CORRECT} THEN {SETPUMP VOLTAGE TO ZERO}• The controller performance would not beas good as PI controller, but it is acceptable.FUZZY LOGIC TO SOLVE OUR DESIREDPROBLEMa>fuzzification: The first step in fuzzy logic is toconvert the measured signal x(which is temperatureand water pressure) into a set of fuzzy variables.This is called fuzzy classification or fuzzification.It is done by giving values (these will be our fuzzyvariables) to each of a set of membership functions.The values for each membership function arelabeled µ(x), and are determined by the originalmeasured signal x and the shapes of themembership functions. A common fuzzy classifiersplits the signal x into five fuzzy levels as follows:1. LP: x is large positive2. MP: x is medium positive3. S: x is small4. MN: x is medium negative5. LN: x is large negative• Membership functions for these five fuzzylevels are shown in figure 2.So,for example, thevalue(or fuzzy variable)for the MP membershipfunction and a signal value of x=2.5v isµmp(2.5)=0.5.III. RESEARCH BLOCK DIAGRAM
  3. 3. Utsav modi, Parita patel / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.1067-10701069 | P a g eFig2a: Membership Functions for zeromembership(s: x is small), medium positivemembership (MP), large positive membership(LP).Figure 2b: The complete set of membershipFunctions for five level fuzzification.Fig 3: Fuzzy block diagram in our desire projectFig4: Detail block diagram of fuzzy processingREFERENCES[1] http://www.egr.msu.edu/classes/ece480/goodman/ForMinipro[2] jects/Lab3.pdf[3] http://www.egr.msu.edu/eceshop/Parts_Inventory/datasheets/74ls12. pdf[4] http://www.egr.msu.edu/eceshop/Parts_Inventory/datasheetZ/sn7407 .pdf[5] http://www.egr.msu.edu/eceshop/Parts_Inventory/datasheets/sn7407. pdf[6] http://ulcape.org/wiki/Tutorial-PIC_Programming_Basics[7] A. Di Stefanos �machine a state,published in his article[8] di un timer digital programmable on the257n of the �Fare Electronic[9] Manish Agarwal Department ofMechanical Engineering Indian Instituteof Technology, Kharagpur - 721302, India[10] "Designing With Fuzzy Logic" by KevinSelf, IEEE SPECTRUM, November 1990,42:44,105.[11] "Fuzzy Fundamentals" by Earl Cox, IEEESPECTRUM, October 1992, 58:61. Notesfrom this article constitute the core of this
  4. 4. Utsav modi, Parita patel / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.1067-10701070 | P a g etutorial.[12] "Fuzzy Logic Flowers In Japan" by DanielG. Schwartz & George J. Klir, IEEESPECTRUM, July 1992, 32:35.[13] "Clear Thinking On Fuzzy Logic" byLawrence A. Berardinis, MACHINEDESIGN, 23 April 1992, 46:52.[14] "Fuzzy Controller Challenges 8-bitMCUs", COMPUTER DESIGN,November 1995.[15] "Dishwasher Cleans Up With FuzzyLogic", MACHINE DESIGN, 23 March1995.[16] "How To Design Fuzzy LogicControllers", MACHINE DESIGN, 26November 1992.[17] "A Case For Fuzzy Logic" by ByronMiller, EMBEDDED SYSTEMSPROGRAMMING, December 1995,42:70.[18] Fuzzynet technical case studies[19] http://www.aptronix.com/[20] Technical manual of washing machines,Samsung electronics ;[21] http://www.samsungelectronics.com.my/washing_machine/tech_info /index.html[22] Weijing Zhang, Applications Engineer,Aptronics Incorporated, Copyright © 1992by Aptronix Inc.[23] MP LAB website and informationwww.mplab.com[24] ‖FUZZY LOGIC WITHENGINEERING APPLICATION ―byTIMOTHY J.ROSS.[25] Chip manual with detailing ofconfiguration of the chipwww.microchip.com[26] Information of the chip burnerhttp://www.sunrom.com..[27] http://www.ideawicket.com[28] www.freshersworld.com[29] www.google.com[30] Magazine ―e-STYLE‖[31] Magazine ―ELECTRONICS FOR YOU‖.[32] Thermocouple informationwww.omega.com[33] Control system informationwww.control-system-principles.co.uk[34] www.control-systems-principles.co.uk[35] fuzzy technical studies[36] www.aptronix.com[37] technical manual of washing machines,Samsung electronics:[38]www.samsungelectronics.com.my/washing_machine/tech_info/inde x.html[39] weijing electronics, ―Applicationengineer‖[40] Pagni, Poluzzi, Lo Presti, Rizzotto"Automatic Syntesis AnalysisImplementation of a Fuzzy Controller"IEEE International Conference on FuzzySystems 1993, San Francisco, pp. 105-110.[41] Neichfeld, Klinche, Menke,Nolles,Kunemund "A General PurposeFuzzy Inference Process" IEEEInternational Conference onMicroelectronics for Neural Networks andFuzzy Systems, Turin 1994, pp310-318.pp. M. Sugeno "Industrial Applications ofFuzzyControl" Elsevier Science Pub. Co.1985 – see also Fuzzy Logic Handbookfor use with Matlab pp. 2-53. F. Boschetti,A. Gabrielli, E. Gandolfi, M.Masetti,"Fuzzy Logic Oriented to Active RuleSelector and Membership FunctionGenerator for High Speed Digital FuzzyMicroprocessor " - World Congress onNeural Networks, July 17-21 1995Washington -Vol. 393 – 97[44] R. Caponetto, M. Lavagna, M. Lo Presti,A.Milazzotto "Genetic Algorithms andNeuro-Fuzzy Systems for AutomaticController Design" Proceedings ofCIFT’95, Trento Italy June 8-10 95, pp38-47.F. Boschetti, A. Gabrielli, E.Gandolfi, M.Masetti, M. Russo "DigitalMembership[45] Function Generators and No-ContributeRule Eliminator for High Speed FuzzyArchitectures "- World Congress onNeural Networks July 17-21 1995Washington - Vol.2 pp. 625 – 629.[46] D, Falchieri, A. Gabrielli, E. Gandolfi,M.Masetti "Design and Realization of aTwo Input Fuzzy Chip Running at a Rateof 80 ns‖Annual IEEE Meeting of theNorth America Fuzzy InformationProcessing Society Syracuse, September21-24, 329-335.AuthorsFirst Author- Utsav modi, bachelors ofengineering, Electronics and communicationSecond Author- Parita Patel, bachelors ofengineering, Electronics and communication,

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