A sine wave with amplitude of 1 Km/h;• Bias of 3.5 Km/h (constant);• A frequency of 0.2618 rad/h (yellow graph in Fig. 3).Radiation: We can simulate radiation changes likebefore variables but my compiled software inMATLAB has ability to model the radiation with using the geographical equations that explain in next section. (Green graph in Fig. 3).The soil evaporation model [8, 9]: The FAO Penman-Monteith method is recommended as the sole ETo method for determining reference evapotranspiration.The modified Penman method was considered to offer the best results with minimum possible error in relation to a living grass reference crop. It was expected that the pan method would give acceptable estimates,depending on the location of the pan. The radiation method was suggested for areas where availableclimatic data include measured air temperature andsunshine, cloudiness or radiation, but not measured wind speed and air humidity.The FAO Penman-Monteith method to estimateETo is:() ()() 2234 . 0 1273900408 . 0ue e uTG RETa s no+ + ∆−++ − ∆= (1)()23 . 2733 . 27327 . 17exp 6108 . 0 4098++= ∆TTT(2) P 10 x 0.665e?P C? 3 p −= =62 . 52930065 . 0 2933 . 101 −=zP (4)()+=3 . 27327 . 17exp 6108 . 0TTT e (5)Where:ETO = Reference evapotranspiration [mm day-1],Rn = Net radiation at the crop surface [MJ m-2 day-1],G = Soil heat flux density [MJ m-2 day-1],T = Mean daily air temperature at 2 m height [°C],u2 = Wind speed at 2 m height [m s-1],es = Saturation vapour pressure [kPa],ea = Actual vapour pressure [kPa],es-ea = Saturation vapour pressure deficit [kPa],∆ = Slope vapour pressure curve [kPa °C-1],γ = Psychrometric constant [kPa °C-1].P = Atmospheric pressure [kPa],z = Elevation above sea level [m],e°(T) = Saturation vapour pressure at the airtemperature T [kPa],λ = Latent heat of vaporization, 2.45 [MJ kg-1],Cp = Specific heat at constant pressure, 1.013 10-3[MJ kg-1 °C-1],ε = Ratio molecular weight of water vapour/dry air = 0.622.The control stage: The control stage interfaces the desired soil moisture and the measured soil moisture (from the “soil” stage). This stage is intended to keep the actual soil moisture as close as possible to the desired moisture. Its output is the valve control value, which represents the amount of water that should be added to the soil continuously in order to maintain a minimal deviation. The block diagram of the fuzzycontroller is shown in Fig. 4. As can be seen from this figure, the controller has only one input signal (the difference between thedesired and the actual soil moisture values) and one output parameter (the valve control). This makes the system very simple and straightforward. The input values are defined in the range [-100, 100] and the output values are defined in the range [0, 100]. By doing so, the controller can specify the valve operation in the desired range. The rules for the controller are very simple. Thereare only five rules (one rule per input variable). These rules are presented in Fig. 5
. The block diagram of the on/off controller with hysterics and without it is shown in Fig. 6. In simple on/off controller the valve is opening when desired soil moisture is more than measured soil moisture but in on/off controller that equipped to hysterics the valve is opening when desired soil moisture is more thanmeasured soil moisture at least of the hysterics value. moisture in other words system isn't stablecompletely.2. In on/off controller system with hysterics, increase oscillations of actual soil moisture, the on/off of valve, rate of amortization and consumption ofenergy when hysterics value decrease.3. In on/off controller system without hysterics,oscillations of actual soil moisture, the on/off of valve. And consumption of energy decreasesrelative to one with hysterics instead the wastage of water and water stress in soil and plant increase.4. The actual soil moisture tracks the desired onewithout any oscillation in fuzzy controller system5. The difference between them (the "error") isreasonable and it is quite steady (around 2-3%).This shows that the irrigation controller is stable.6. In fuzzy controller system the on/off of valve and consumption of energy is less than on/off controller system and so is prevented of water stress in soil and plant.7. Each of three controller system, the source-generation model allows the user a wide variety ofclimate combinations; therefore, the controller can operate in any circumstances.8. The main target -to design a cheap and reliable irrigation controller -has been achieved in fuzzy controller system.CONCLUSIONSThis paper has compared three systems equipped to on/off with hysterics, simple on/off and fuzzycontroller with each other. First, it explained thegeneral architecture and its components. Than some examples showed that the system operates within the proper range and is stable. Consequently fuzzycontroller system had more ability as compared with another system. It is important to note that such system can save a lot of water and is very cheap to implement. The fuzzy rules are simple (as shown in Fig. 8), therefore making the system attractive to use by all types of agriculturists. REFERENCES1. Evans, R., R.E. Sneed and D.K. Cassel, 2006.Irrigation scheduling to improve water and energy use efficiencies, North Carolina Cooperativeextension Service (AG 452-4).2. Reuter, D.C. and R.S. Everett, 2000. Controltheory and applications: Neural-fuzzy controller for lawn irrigation.3. Zazueta, F.S., A.G. Smajstrla and G.A. Clark,1994. Irrigation system controllers. Institute ofFood and Agriculture Science, 大棚自动滴灌系统英文文献和中文翻译(2):http://www.751com.cn/fanyi/lunwen_64424.html