A hydroponic greenhouse fuzzy control system: design, development and optimization using the genetic algorithm

Abstract

Aim of study: The design and development of a hydroponic greenhouse fuzzy control system.
 Area of study: The evaluation was performed using experimental data obtained from the literature. The construction and evaluation of the fuzzy control hydroponic greenhouse system was carried out in a greenhouse in Tehran, Iran.
 Material and methods: The greenhouse environmental conditions, including temperature, humidity, and carbon dioxide, were controlled. The design of a fuzzy controller begun with the selection of linguistic variables, process status, and input and output variables. The fuzzy control system consisted of three modules: 1) fuzzy module, 2) cost function, and 3) genetic algorithm for the adjustment of the greenhouse environmental conditions.The next step was to select a set of linguistic rules and the type of fuzzy inference process. The rules were set once, and the fuzzy set and output value needed to be specified after the inference, along with the development of a non-fuzzy strategy.
 Main results: The mean temperatures provided by the fuzzy control system during the day and night were 34.25°C and 23.22°C, respectively, which were improved to 31.17°C and 21.96°C after optimization. The mean humidity was 39.4% and 56.5% during the day and the night, respectively, which turned 60.22% and 74.59% after optimization. The control system also achieved desirable conditions in terms of CO2 amount.
 Research highlights: The results showed that the measured values of temperature and relative humidity of the greenhouse were improved after optimization with genetic algorithm.