Modeling Key Parameters for Greenhouse Using Fuzzy Clustering Techniques

Abstract

The clustering techniques are usually used in classification and pattern recognition. Moreover, fuzzy logic is used for system modeling when the information is scarce, inaccurate or its behavior is described using a complex mathematical model. As example of this type of system, a greenhouse is considered, where the variables are: in-house and out-house temperature, humidity for both inside and outside the greenhouse and wind direction. These variables show a dynamic and non-linear behavior; being the in-house temperature and internal humidity the variables of concern for the greenhouse control and modeling. In this project, the development and implementation of three clustering algorithms, being fuzzy K-means, Fuzzy C-means and fuzzy clustering subtractive, is presented. This project is used as the foundation for the design of fuzzy systems and its application in temperature and humidity modeling of a greenhouse used as a laboratory of biotronics at the Universidad Autonoma de Queretaro.

A Systematic Review of Greenhouse Humidity Prediction and Control Models Using Fuzzy Inference Systems

“…ese models must be related to the external influences of outdoor climatic conditions (such as solar radiation, outdoor air temperature, wind speed, etc.) and to the actions carried out (such as ventilation, cooling, heating, among others) [6,13,19,20].…”

“…Fuzzy modelling provides a framework for modelling complex nonlinear relationships. Compared to traditional mathematical modelling, fuzzy modelling possesses some distinctive advantages, such as an understandable reasoning mechanism, the ability to take linguistic information from human experts and combine it with numerical data, handling numerical and linguistic information in the same context, the ability to execute complex nonlinear functions with simple models, and representation in linear time-invariant local models [2,5,7,10,12,13,20].…”

A Takagi-Sugeno Fuzzy Model for Greenhouse Climate

“…Identification based on Takagi-Sugeno (TS) fuzzy model was used in [12]. In [13], clustering was utilized to acquire the main modeling greenhouse parameters. In [14], hierarchical strategy was used to minimize the number of fuzzy rules in the modeling of the system.…”

Modelado difuso Takagi-Sugeno para sintonizar un controlador de calefacción en invernaderos

“…3. Estos controles locales son definidos para cada regla difusa con el fin de encontrar la señal de control que se aplicará en el sistema, las reglas del control difuso están dadas por (9).…”

“…En [7,8] y se emplean mínimos cuadrados para obtener los consecuentes de las reglas, en el presente estudio se usará esta técnica siendo muy similar a la mostrada también en [9]. No sólo existen modelo difusos con la aplicación a invernaderos, en [10] se presenta un modelo basado en algoritmos evolutivos.…”