Improving Performance of the Greenhouse by Using Fuzzy Logic Controller (In case Ethiopian greenhouse System)

Abstract

Greenhouse are populare in agriculture for several reasons: extended growing seosons, protecting from exterm weather, pest and disease control, improved crop quality, water conservation and higher crop yields, Overall, greenhouse choice for a around the world. In a specilized plant factory operating in challenging environments the key parameters that require control are temperature and humidity. Controlers like adaptive and proportional integral derivative (PID) have been developed and tested in real-world settings. Eventhough they did not consider constraints and parameter interactions, they showed outcomes of effectiveness of the control system. However, it is currently impractical to apply the same approach for regulating the parameters. The primary goal of this study is to show the advancement in greenhouse performance achieved by implementing an intelligent control system based on fuzzy logic controllers. By integrating error-based analysis and considering transient response criteria, the proposed system significantly enhances the overall efficiency of Ethiopian greenhouse production. The designed controller aims to reduce modeling error while also reducing settling error and overshoot. The controllers were developed and simulated using MATLAB/Simulink to evaluate the efficacy of the suggested control approaches. By using trial-error method the response shows the result have been compared with the PID controller. Under varied psychrometric circumstances throughout the summer, the set point tracking and disturbance rejection performance tests were run. Utilizing criteria like overshoot, settling time, recovery time, and perturbance peak values, the performance of the controllers is evaluated. The tracking test focuses on analyzing the indoor temperature result to carry out the parameters. which the plant using the temperature as set-point 26°C and 20% of the interior air humidity, so the performance measure result for temperature rise time 2.080 min, settiling time 2.861min,overshoot 1.073min and IAE 6.666, and for humidity rise time 2.498 settiling time 3.598 min,overshoot 0.592 min and IAE 8.014. Overall, the performance metrics obtained from both performance tests consistently demonstrated that the FLC controller for indoor temperature and humidity out performs the PID controller in the designed system.