Irrigation Fuzzy Controller Reduce Tomato Cracking

Abstract

Abstract-Sunlight heats the greenhouse air temperature and tomato cracking decreases marketable product up to 90%. A shade screen reduced incoming radiation during warm and sunny conditions to reduce tomato cracking. A fuzzy controller managed greenhouse irrigation to reduce tomato cracking using as variables solar radiation and substrate temperature. The embedded controller presented 9 rules and three assumptions that made it operate better. Signal peaks were removed and control actions could take place ten minutes after irrigation. Irrigation was increased during the peak hours from 12:00 to 15:00 h when it was required by the fuzzy controller; meanwhile water containing the nutrient solution was removed during very cloudy days with limited photosynthesis. After three continuous cloudy days irrigation should be scheduled to avoid plant nutrient problems. Substrate temperature in volcanic rock can be used as real time irrigation sensor. Tomato cracking decreased to 29% using the fuzzy controller and canopy temperature never exceeded 30ºC.

Intelligent Climate Control System inside a Greenhouse

“…The need to improve these climatic conditions has called for advanced control algorithms due to the complexity and nonlinearity of the greenhouse system. Many researchers have developed several control strategies to improve the indoor microclimate such as Proportional -Integral -Derivative controller (PID controller) [1], Neural Network [2,3], the PI controller (SSODPI and PI-SSOD event controllers) [4], Adaptive Neuro-fuzzy controller [5,6,7,8], Genetic algorithm [9], Optimal control [10], Predictive Neural Control [11], four control techniques have been developed [12]: Adaptive Neuro-Fuzzy Control (ANFIS), Fuzzy Logic Control (FLC), PI Control and Artificial Neural Network Control (ANN), to adjust the temperature inside the greenhouse, and a Fuzzy Logic Controller (FLC) [13,14] which is a valuable element in the control of hardly identifiable and non-linear systems. Also, several studies have established the importance and usefulness of the FLC controller and its tool to solve the problem of complexity and non-linearity of the greenhouse system [15] from which presented a comparative study of a basic fuzzy controller and optimized fuzzy controllers to show their advantages and disadvantages.…”