ANFIS-based climate controller for computerized greenhouse system

Abstract

The greenhouse climate system is very hard to manipulate because the variables involved are closely correlated. This study aims to enhance the regulation performance of greenhouse climate system based on adaptive neural-fuzzy inference system (ANFIS). The ANFIS is a hybrid technique that incorporates the fuzzy logic theory and artificial neural network algorithms. The employed control system has the ability to stabilize the climatic variables inside greenhouse system at required levels for crops development. The datasets utilized to train ANFIS model was obtained by implementing a fuzzy logic controller under MATLAB Simulink environment. The feasibility, reliability and robustness of the adopted strategy have been experimentally studied. The experiments conducted in real-time show that the proposed technique provides good tracking, short response time and high robustness with regard to outside perturbations and non-linear behaviors of greenhouse systems.