Design of efficient hydroponic nutrient solution control system using soft computing based solution grading

This paper presents an efficient hydroponic nutrient solution control system whose system parameters are optimized using genetic algorithm. A novel mamdani fuzzy inference system (FIS) that grades the quality of solution for a given set of control parameters has been used as its fitness function. The FIS evaluation function has been designed using expert opinion from researchers at Murugappa Chettiar Research Centre, India. To evaluate the performance of the proposed algorithm, a virtual hydroponic nutrient control system with a solution monitoring unit was designed using Labview. The designed algorithm demonstrated better convergence efficiency and resource utilization compared to conventional error function based nutrient solution control systems.