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Greenhouse Climate Controller Using Fuzzy Logic Programming

Greenhouse Climate Controller Using Fuzzy Logic Programming. Anantharaman Sriraman September 2, 2003. Purpose of GHCC. It takes care of maintaining a protected environment despite fluctuations of external climate

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Greenhouse Climate Controller Using Fuzzy Logic Programming

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  1. Greenhouse Climate Controller Using Fuzzy Logic Programming Anantharaman Sriraman September 2, 2003 GreenHouse Climate Controller Fuzzy Logic Programing

  2. Purpose of GHCC • It takes care of maintaining a protected environment despite fluctuations of external climate • It acts as a program memory, which can be operated by the grower as a tool to steer their cultivation GreenHouse Climate Controller Fuzzy Logic Programing

  3. Advantages of GHCC • Energy Conservation • Better productivity of plants • Reduced human intervention GreenHouse Climate Controller Fuzzy Logic Programing

  4. Environmental factors Major Factors • Temperature of the inside air • Relative humidity of the inside air • Sunlight Minor Factors • Wind speed • Wind direction • Rate of transpiration GreenHouse Climate Controller Fuzzy Logic Programing

  5. Control Actuators • Thermal System • Humidification System • Lighting system • Thermal shade system • CO2 generator • Performance of the system GreenHouse Climate Controller Fuzzy Logic Programing

  6. Fuzzy Logic • an alternative design methodology • linear and non-linear systems for control • lower development costs • superior features • better end product performance • market faster • more cost-effectively GreenHouse Climate Controller Fuzzy Logic Programing

  7. Fuzzification • Measure the values of input variables • Performs a scale mapping that transfers the range of values of input variables into corresponding universes of discourse, • Performs the function of fuzzification that converts input data into suitable linguistic values, which may be viewed as labelsof fuzzy sets. GreenHouse Climate Controller Fuzzy Logic Programing

  8. Knowledge Base • Comprises knowledge of the application domain and the attendant control goals. It consists of a “database” and a “linguistic (fuzzy) control rule base:” • The database provides necessary definitions, which are used to define linguistic control rules and fuzzy data manipulation in an FLC. • The rule base characterizes the control goals and control policy of the domain experts by means of a set of linguistic control rules. GreenHouse Climate Controller Fuzzy Logic Programing

  9. The decision-making logic • It is the kernel of an FLC. It has the capability of simulating human decision-making based on fuzzy concepts, implication and the rules of inference in fuzzy logic GreenHouse Climate Controller Fuzzy Logic Programing

  10. The defuzzification inference • Scale mapping, which converts the range of values of output variables into corresponding universe of discourse, • Defuzzification, which yields a non-fuzzy control action from an inferred control action. • A defuzzifier converts an inferred fuzzy control action into a crisp one GreenHouse Climate Controller Fuzzy Logic Programing

  11. Comparison of Conventional & Fuzzy Design GreenHouse Climate Controller Fuzzy Logic Programing

  12. Advantages • Reduces Design Development Cycle • Simplifies Design Complexities • Improve time to market • Better for non Linear system • Improve control performance • Reduces hardware cost GreenHouse Climate Controller Fuzzy Logic Programing

  13. Greenhouse Layout GreenHouse Climate Controller Fuzzy Logic Programing

  14. Function of Controller GreenHouse Climate Controller Fuzzy Logic Programing

  15. Role of FLC in GHCC GreenHouse Climate Controller Fuzzy Logic Programing

  16. Input Variables • Difference in temperature between inside greenhouse & optimum must be maintained in greenhouse [-10 to +10 ºC] • Difference in temperature between outside greenhouse & optimum must be maintained in greenhouse [-20 to +20 ºC] • Difference in R-Humidity between inside greenhouse & optimum must be maintained in greenhouse [0 to 100 %] • Difference in R-Humidity between outside greenhouse & optimum must be maintained in greenhouse [0 to 100 %] • Sunlight incident on the greenhouse roof [0 to 20 W/m2] • Seasonal Cloudiness which reduces the sun’s radiation [0 to 100 %] • Wind speed [0 to 100 mph] • Wind direction with respect to the direction of the ventilation system of the greenhouse • Measurement error of the sensing system (-4 to 4) • Change in Error of the measurement of the sensing system (-1 to 1) GreenHouse Climate Controller Fuzzy Logic Programing

  17. Output Variables • Thermal system (0 to 100 %) • Ventilation & humidification system (0 to 100 %) • Thermal shade system (0 to 100 %) • CO2 generation system (0 to 100 %) • Forced ventilation system (0 to 100 %) • Performance of the system (0 to 100 %) GreenHouse Climate Controller Fuzzy Logic Programing

  18. FLC System GreenHouse Climate Controller Fuzzy Logic Programing

  19. Input Membership Function GreenHouse Climate Controller Fuzzy Logic Programing

  20. Input MFs GreenHouse Climate Controller Fuzzy Logic Programing

  21. Input MFs GreenHouse Climate Controller Fuzzy Logic Programing

  22. Output MFs GreenHouse Climate Controller Fuzzy Logic Programing

  23. Output MFs GreenHouse Climate Controller Fuzzy Logic Programing

  24. Rules-1 GreenHouse Climate Controller Fuzzy Logic Programing

  25. Rules-2 GreenHouse Climate Controller Fuzzy Logic Programing

  26. Rules-3 & 4 GreenHouse Climate Controller Fuzzy Logic Programing

  27. Rules 5 & 6 GreenHouse Climate Controller Fuzzy Logic Programing

  28. GUI GreenHouse Climate Controller Fuzzy Logic Programing

  29. THANK YOU Questions? GreenHouse Climate Controller Fuzzy Logic Programing

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