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International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012ISSN 2229-55181Fuzzy Logic Approach for BoilerTemperature & Water Level ControlAnabik Shome, Dr. S.Denis AshokAbstract— Boiler is the main component in generating steam in thermal power generation units and its control is very important in manyapplications. In present situation conventional PID control is being used for this purpose. These conventional controllers in power plantsare not very stable when there are fluctuations and, in particular, there is an emergency occurring. Continuous processes in power plantand power station are complex systems characterized by nonlinearity, uncertainty and load disturbances. The conventional contr ollers donot work accurately in a system having nonlinearity in it. So, an intelligent control using fuzzy logic is developed to m eet the nonlinearity ofthe system for accurate control of the boiler steam temperature and water level.Index Terms— Boiler temperature control, Conventional controllers, Fuzzy logic, Fuzzy logic control, Fuzzy Inference System,Microcontroller, PID control, Water level control.—————————— ——————————1 INTRODUCTIONTemperature controllers are needed in any situation requiring a given temperature be kept stable. This can bein a situation where an object is required to be heated,cooled or both and to remain at the target temperature (setpoint), regardless of the changing environment around it.Temperature controllers are used in a wide variety of industries to manage manufacturing processes or operations.There are several reasons for using automatic temperaturecontrols for steam applications.For some processes, it is necessary to control the product temperature to within fairly closelimits to avoid the product or material being processed beingspoilt.Steam flashing from boiling tanks is a nuisance that notonly produces unpleasant environmental conditions, but canalso damage the fabric of the building. Automatic temperaturecontrols can keep hot tanks just below boiling temperature.Also for economy, quality and consistency of production, saving in manpower, comfort control, safety and to optimize ratesof production in industrial processes boiler temperature control is necessary.Conventional control system in power station adopts PIDcontroller. Unfortunately, large inertia and lag appear, whenwe use PID controller which could not adjust the temperatureto good scope. On the other hand, drawbacks of this systemare terrible robustness and fixed PID parameter which couldnot regulate with variation of the object. Because there arenonlinearity, variation, disturbance and change of objectivearchitecture, the system could not attain well result by usingPID parameter which previously set.Since the introduction of fuzzy set theory by Zadeh and thefirst invention of a fuzzy controller by Mamadani, fuzzy control has gained a wide acceptance, due to the closeness of ��Anabik Shome is currently pursuing M.Tech in Mechatronics Engineeringin VIT University, Vellore-632014, India, and PH- 917598535829.E-mail: [email protected]. S. Denis Ashok is currently the divisional leader of M.Tech Mechatronics Engineering in VIT University, Vellore-632014,India,PH- 919444868585.E-mail: [email protected] logic to human thinking, and has found applications insome power plants and power systems. It provides an effective means of converting the expert-type control knowledgeinto an automatic control strategy. A fuzzy control mainlysimulates control experience of human and gets rid of controlobject. It discusses definite nature, fuzzy and imprecise information system control in the real world.2 CURRENT SCENARIO OF BOILER CONTROLIn electric boilers, the resistance of the water to the passage ofelectricity generates heat and steam. No part of the generatoris ever hotter than the water or steam itself. Therefore, no baking of solids or residue occurs. Furthermore, when the electrode tips become uncovered, no current can pass, hence, nolow water damage can occur. Within the pressure vessel of thegenerator, a cylinder, open at the bottom, is welded to the inside of the upper-head of a pressure vessel. This cylinder divides the vessel into two concentric chambers. The outerchamber (K) is the regulating chamber. The inner chamber (J)is the generating chamber. Suspended within the generatingchamber are the electrodes (N). Electric power (P) is easilyconnected to the three electrode terminals. A prescribed quantity of Electrolyte is dissolved in water and poured into thegenerator through the hand fill (G). This Electrolyte remains inthe generator until drawn off with the water through the drainvalve (M). Electric power is turned on, and heat is generatedby the resistance of the water to the passage of current between the solid electrodes. Steam produced in the generatingchamber (J) flows through the steam valve outlet (I), and viathe steam header (E), through the pressure regulating valveor(C) to the regulating chamber (K). Before the electric boiler isturned on, water levels would be balanced. Adjusting thescrew on the pressure regulator valve (D) sets the desiredpressure. When the system is turned on, air is automaticallyexhausted through the air eliminator (A), which closes whenheated by the steam. If the steam consumed is less than maxi-IJSER 2012http://www.ijser.org
International Journal of Scientific & Engineering Research Volume 3, Issue 6, June-20122ISSN 2229-5518mum, pressure built-up in the generator chamber until itreaches the pressure limit set by the pressure regulator. At thispoint the pressure regulator valve partially closes, reducingthe amount of steam entering the regulating chamber. Thisunbalances the system momentarily, permitting the water torise in the regulating chamber due to the higher pressure condition in the generating chamber. As the water level drops inthe generating chamber the electrodes are progressively exposed, and the amount of steam being generated decreases.Inasmuch as current input is proportional to the immersedarea of the electrodes, the falling water level reduces the electric input. Conversely, if heavy use of steam tends to lower thedesired pressure, the regulating valve opens wide, allowingmore steam into the regulating chamber. This forces waterback into the generating chamber, increasing the flow of current and rate of steam production by completely envelopingthe electrodes. The water level in both chambers is rarely balanced. This condition occurs only at full load.sensor output and level indicator output as the two inputs forthe Fuzzy Inference System.After fuzzification of the inputsand applying suitable rules and defuzzifying the output themicrocontroller generates appropriate control signals.3.1 T EMPERATURE MONITORING & CONTROL3.1.1 Temperature Monitoring The temperature is measured using the sensor.The sensor output is compared with the set value.The error or deviation from the set value is given asan input to the fuzzy logic control system.Fig.3. Interfacing of sensor with microcontroller3 PROPOSED METHODOLOGYThe proposed method consists of two sections.First section isto develop a steam temperature monitoring and control system and the second section consists of water level control.Forboth of the sections Fuzzy Logic Control will be used.A microcontroller will be programmed with the fuzzyknowledge base rule. The temperature sensor will be interfaced with the microcontroller to monitor the steam temperature and a level indicator circuit will be interfaced with themicrocontroller which will indicate the water level inside theboiler chamber.The microcontroller will take the temperatureIJSER 2012http://www.ijser.orgFig.4. Setup for temperature monitoring
International Journal of Scientific & Engineering Research Volume 3, Issue 6, June-20123ISSN 2229-55183.1.2 Temperature Control INPUTSThe Fuzzy Inference system fuzzifies the inputs andapplies suitable rules and calculates the defuzzifiedvalue.It then decides the suitable control action to be performed.The microcontroller gives command to perform therequired control action to turn the heater ON/OFFfor safe operation of the boiler.NEG Ne gativeVS Ve ry SmallZE Ze roS SmallVS Ve ry SmallM Me diumS SmallHi HighM Me dium/Mode rateH HighOUTPUTSHTRMAX Heater MaximumPONVCLOSED Pump On Valve ClosedHTRMOD Heater ModeratePONVOPENLESS Pump On Valve Open lessHTROFF Heater OffPOFFVOPENFULL Pump Off Valve Open FullFig.7. Input/Output Fuzzy InterpretetionsFuzzy rules:Fig.5. Setup for Temperature control3.2 LEVEL CONTROLThe water level control is also an important parameter for boiler control.The water level inside the boiler chamber needs to becontrolled because of changing load demand.When there is aneed of more steam water level should be high and when there isa need of less steam the water level should be low.To maintainthe water level inside the boiler chamber a level indicator circuitis used and the circuit is interfaced with the microcontroller.TheFuzzy Inference System stored inside the microcontroller thenfuzzifies the inputs and applies suitable rules and then gives thedefuzzified values which is then processed by the microcontrollerto give the suitable control action to turn ON/OFF the inlet pumpand OPEN/CLOSE the outlet valve.Fig.8. Input Membership function: STEAMTEMP4 FUZZY INFERENCE SYSTEMFig.9. Input Membership function: WATERLEVELFig.6. Block diagram of fuzzy inference systemFig.10. Output Membership function: HEATERIJSER 2012http://www.ijser.org
International Journal of Scientific & Engineering Research Volume 3, Issue 6, June-20124ISSN 2229-55185.2 C-Program Simulated resultsFig.11. Output Membership function: PUMPANDVALVE5 RESULTSThe fuzzy control model for boiler temperature and water levelcontrol is simulated using MATLAB and also verified using CProgram.The steam temperature monitoring & control portion isalso verified using a prototype model.The level control portion isverified using MATLAB and C-Program but not verified experimentally due to some hardware limitations.OFig.14. C-Program simulated output when Steam temp 37 C andWater level 3cm5.1 MATLAB Simulated ResultsOOFig.12. MATLAB simulated output when Steam temp 37 C andWater level 3cmOFig.13. MATLAB simulated output when Steam temp 100 C andWater level 9cmFig.15. C-Program simulated output when Steam temp 100 C andWater level 9cm5.3 Experimentally Verified Results for SteamTemperature Monitoring & ControlOFig.16. LCD displaying temp 37 C & Green LED correspondsHeater ON with Maximum IntensityIJSER 2012http://www.ijser.org
International Journal of Scientific & Engineering Research Volume 3, Issue 6, June-20125ISSN 2229-5518LCD DISPLAYINGTEMPERATURE 100OC[2]E.H. Mamdani,”Application of fuzzy algorithms for control of simple dynamicplant,” PROC. IEE, Vol. 121, No. 12, DECEMBER 1974.[3]Liangyu Ma and Kwang Y. Lee,” Neural Network Based Superheater SteamTemperature Control for a Large-Scale Supercritical Boiler Unit,” 978-1-4577-10025/11/ 26.00 2011 IEEE.[4]M. E. Flynn and M. J. 0’ Malley,” A Drum Boiler Model for Long Term PowerSystem Dynamic Simulation,” IEEE Transactions on Power Systems, Vol. 14,No. 1, February 1999.[5]Wei Wang, Han-Xiong Li, and Jingtao Zhang,” Intelligence-Based Hybrid Control for Power Plant Boiler,” IEEE Transactions on Control Systems Technology,Vol. 10, No. 2 March 2002.[6]Xiang-jie Liu and Felipe Lara-Rosano,” Generalized Minimum Variance Controlof Steam-Boiler Temperature using Neuro-Fuzzy Approach,” Proceedings of the5'WorId Congress on Intelligent Control and Automation, Hangzhou, P.R.China, June 15-19. 2004.[7]Yu Yanzhi,Xu Haichuan,Lv Junxian, Chen Duoggang ,Dong Gongjun,ShenBo and Liu Sheng, “600 MW Supercritical Boiler’s Main Steam Temperature Control Analysis,” WASE International Conference on Information Engineering,2010.[8]GuXiuPing, “Study on the Superheated Steam Temperature Control System Basedon Fuzzy-Neural Network [0], “Tianjin University, 2004[9]K. K. Tang, Q. G. Wang, and C. C. Hang, Advances in PID Control. NewYprk: Springer-Verlag, 1999OFig.17. LCD displaying temp 100 C & Red LED correspondsHeater OFF.5.4 Discussion about the ResultFrom the above displayed figures we can observe that thetemperature monitoring & control portion as well as the levelcontrol portion is simulated successfully in MATLAB and alsousing C-Program.The temperature monitoring & control portion is also experimentally verified using a prototype model.6 CONCLUSIONThe fuzzy logic based boiler temperature monitoring & controland Water level control inside the boiler chamber is simulatedsuccessfully and also the temperature monitoring & controlportion is experimented successfully using a prototype modeland the results are also verified verified.So, we can concludethat the fuzzy logic based boiler temperature and level controlis working properly and the results obtained are very promising and satisfactory.7 FUTURE SCOPESFuzzy logic is a very emerging intelligent control methodwhich can be applied successfully in nonlinear as well as inlinear systems. Till now the conventional controllers like PIDcontrollers are used in boiler temperature control applicationsbut it has some disadvantages and errors when there is variation of load and nonlinearity arises in the system. But intelligent control system like fuzzy control works efficiently underthese environments and can be easily implemented as observed in the experiment performed on the prototype modeland using more ranged temperature sensors and level indicators and more powerful microcontrollers it can be implemented easily in industrial boiler and other steam temperaturecontrol applications as well as in other temperature and waterlevel control applications.REFERENCES[1]Chuntao Man, Jia Li, Lanying Wang and Yantao Chi,” The Fuzzy PID ControlSystem for Superheated Steam Temperature of Boiler,” The 6th International Forumon Strategic Technology, 2011.[10] Fan Yongsheng, Xu Zhigao and Chen Laijiu, “Study of Adaptive Fuzzy Controlof Boiler Superheated Steam Temperature Based on Dynamic Mechanism Analysis[J], “Proceedings of the CSEE, 1997, 17 (1) ,23-28[11] T. Sudkamp and R. 1. Hammel, "Interpolation, completion, and learning fuzzyrules,” IEEE Trans. Syst., Man, Cybern., vol. 24, no. 2, pp.332-342, Feb. 1994.[12] I. Benyo, “Cascade generalized predictive control-applications in power plant control,” Oulu University Press, Finland, 2006.[13] H. M. Azlan, "Review of the applications of neural networks in chemical processcontrol—simulation and online implementation," Artificial Intelligence in Engineering, no.13, pp. 55-68, 1999.[14] R. Gencay and T. Liu. "Nonlinear modeling and prediction with feedforward andrecurrent networks," 1997, Physica D 108, pp. 119-134.[15] G. Irwin, M. Brown,, B. Hogg, and E. Swidenbank, " Neural network modellingof a 200MW boiler system," IEEE proceedings-Control theory and Applications,1995, 142(6), pp. 529-536.[16] C.-C. Ku and K. Y. Lee. "Diagonal recurrent neural network for dynamic systemscontrol," IEEE Trans. Neural Networks, 1995, 6(1), pp. 144-156.[17] K. Y. Lee, L. Y. Ma, C. J. Boo, W.-H. Jung, and S.-Ho Kim, "Inverase dynamicneuro-controller for superheater steam temperature control of a large-scale ultrasupercritical (USC) boiler unit," Proc. of the IFAC Symposium on Power Plantsand Power Systems Control, in Tampere, Finland, July 5-8, 2009.[18] K. Y. Lee, L. Y. Ma, C. J. Boo, W.-H. Jung, and S.-Ho Kim, "Intelligent modifiedpredictive optimal control of reheater steam temperature in a large-scale boiler unit,"Proc. of the IEEE Power & Energy Society General Meeting, in Calgary, Canada, July 26-30, 2009.[19] L. Y. Ma, Y. J. Lin, and K. Y. Lee. "Superheater steam temperature control for a300MW boiler unit with inverse dynamic process models," Proc. of the IEEE Power& Energy Society General Meeting, in Minneapolis MN, USA, July 25-29,2010.IJSER 2012http://www.ijser.org
International Journal of Scientific & Engineering Research Volume 3, Issue 6, June-2012ISSN 2229-5518[20] C.-C. Ku, K. Y. Lee, and R. M. Edwards. "Improved nuclear reactor temperaturecontrol using diagonal recurrent neural networks," IEEE Trans. Nuclear Science,1992, 39(6), pp. 2298-2308.[21] B. Widrow, J. McCool, and B Medoff, "Adaptive control by inverse modelling,"12th Asimolar conference on Circuits, Systems and Computers, 1978.IJSER 2012http://www.ijser.org6
controls can keep hot tanks just below boiling temperature. Also for economy, quality and consistency of production, sav-ing in manpower, comfort control, safety and to optimize rates of production in industrial processes boiler temperature con-trol is necessary. Conventional control system in power station adopts PID controller.
