Control System Based on Tuna Swarm Optimization, Fuzzy PID, and MQTT Protocol for Remote Fertilization

Aiming to address the problems of low flow-control accuracy, slow response speed, and difficulties in remote monitoring during precision agricultural fertilization, this study proposes a fertilization flow control method based on the tuna swarm optimization algorithm (TSO) combined with fuzzy PID control. Remote monitoring and cloud-based management of the system are achieved through the MQTT protocol. The proposed method uses the TSO to globally optimize the initial PID parameters and the outputs of fuzzy rules, while fuzzy logic is employed to realize real-time adaptive adjustment of control parameters under nonlinear operating conditions. The experimental results show that the proposed TSO-Fuzzy-PID controller exhibits excellent dynamic performance in fertilization flow control. Compared with the conventional PID controller, the maximum overshoot of the system is reduced from 28.37% to 9.15%, and the settling time is shortened from 111 s to 76 s. The remote communication test results indicate that, during 20 consecutive tests lasting 60 min each, the average communication delay of the MQTT communication link remains within 162–215 ms, the maximum delay does not exceed 300 ms, and the message transmission success rate reaches 99.4%, verifying the good real-time performance and reliability of the system.