Design of an Intelligent Control System for Multifunctional Agricultural Simulator

Crop cultivation involves a series of procedures from sowing till harvesting, making it a time-consuming activity. The crop cycle typically spans four to six months, during which cultivation outcomes are influenced by dynamic environmental and management factors such as water availability, temperature, and humidity. These parameters are collectively referred to as Optimum Cultivation Factors (OCFs). Once the cultivation process starts, poor OCFs may lead to reduced crop growth, leading to heavy economic loss. Historically, lessons learned from previous cultivation cycles have been a primary source for improving agricultural practices. Developing simulators that mimic agricultural environments in a controlled setting can support the analysis of cultivation factors while reducing time and resource requirements. In this study, a multifunctional agricultural simulator with a network of actuators is developed in the MATLAB/Simulink environment. The designed simulator mimics the agricultural field’s real-time environment while maintaining the temperature, humidity, and moisture content with appropriate water provision. Based on real field environmental data, the fuzzy-based membership functions are designed to emulate outdoor agricultural conditions at the laboratory scale. The designed system monitors and controls the actuators, such as water pumps for moisture, a heater for temperature, and a sun simulator for solar irradiation control. The cascaded fuzzy logic controller enables multi-factor environmental assessment by analyzing actuator responses under varying operating conditions, supporting pre-cultivation decision making.