A Multistaged Fuzzy Logic Scheme in a Biobotanic Growth Regulation System

Abstract

A multistaged fuzzy logic control method was used in the development of a bionic botanical growth control system. The growth mode combined fuzzy logic inference with expert knowledge to regulate the growth rate of plants. First, environment factors such as the light, temperature, and water required for plants in different stages of growth were analyzed. Fuzzy logic was then used to establish membership functions, an inference engine, and rule table. An expert database related to plant growth was combined with the fuzzy logic controller to formulate a plant growth control system. Sunflowers were used as a simulated model and the results correspond to the information provided by experts. The proposed model was used to control the growth rate of plants based on data provided in the expert database. The proposed method and results of this study are applicable in the management and control of environments for the growth of crops.