Active Control of the Root Environment for Growth Optimization of Plant in Hydroponics Using an Intelligent Control

摘要

A hydroponic culture system based on intelligent control techniques has the possibility to optimize growth of plants by an active control of the root environment. The paper presents the application of a new intelligent control technique consisting ofneural networks and genetic algorithms for the growth optimization of tomato plants in hydroponics during the seedling stage. The control input is the nutrient concentration of the solution. During the seedling stage, the ratio, TLL/SD, of total leaf length (TLL) to stem diameter (SD) seem to be a good indicator for predicting the future balance between the vegetative growth and the reproductive growth. Higher values of TLL/SD result in better reproductive growth. The optimization problem here is to determine the optimal l-step setpoints of nutrient concentration which maximize TLL/SD. First, TLL/SD as affected by nutrient concentration was identified using neural networks and then the l-step optimal setpoints of the nutrient concentration which maximized TLL/SD were sought through simulation of the identified model using genetic algorithms. The optimal setpoints obtained here significantly increased the values of TLL/SD and promoted the reproductive growth. The results showed that an intelligent control technique proposed here is quite useful for realizing the growth optimization of plants in hydroponics.