Scientific researchers have applied newly developed technologies, such as sensors and actuators, to different fields, including environmental monitoring, traffic management, and precision agriculture. Using agricultural technology to assist crop fertilization is an important research innovation that can not only reduce the workload of farmers, but also reduce resource waste and soil pollution. This paper describes the design and development of a water-fertilizer control system based on the soil conductivity threshold. The system uses a low-cost wireless sensor network as a data collection and transmission tool and transmits the data to the decision support system. The decision support system considers the change in soil electrical conductivity (EC) and moisture content to guide the application of water-fertilizer, and then improves the fertilization accuracy of the water-fertilizer control system. In the experiment, the proposed water-fertilizer control system was tested, and it was concluded that, compared with the existing traditional water-fertilizer integration control system, the amount of fertilizer used by the system was reduced by 10.89% on average, and it could save 0.76–0.87 tons of fertilizer throughout the whole growth period of cotton.

An appropriate pH value of liquid fertilizer can enable crops to better absorb nutrients from fertilizers. However, the mixed liquid fertilizer with high concentration of liquid fertilizer and irrigation water has a high pH value, which affects the absorption of nutrients by crops. Therefore, the precise regulation of liquid fertilizer pH value is an important link to realize the integration of water and fertilizer in modern agriculture. Due to pipeline transportation and diffusion of the regulating liquid and liquid fertilizer, the pH value control system has the characteristics of time-varying, non-linear and time-delayed models, and it is difficult for ordinary controllers to accurately control the pH value of liquid fertilizer. Therefore, modern agriculture urgently needs a controller that can adapt to non-linear and uncertain systems. According to the characteristics of the pH regulation process of liquid fertilizer, this study proposes and designs a modified fuzzy-PID-Smith predictive compensation algorithm, which adds the fuzzy-PID algorithm to the predictor of the conventional Smith algorithm to compensate for the error between the actual and theoretical models in order to reduce the decline of control quality caused by the model mismatch to the control system. To verify the practicability and robustness of the algorithm in practical applications, a liquid fertilizer pH value control system with STM32F103ZET6 as the control core was developed. The pH control system with fuzzy-PID and Smith algorithm as controller was used as the control group. The model was simulated and tested under two conditions of exact matching and imprecise matching, and performance tests were carried out under different output flow rates. The results showed that the maximum overshoot of the modified fuzzy-PID-Smith predictive compensation algorithm was significantly less than that of the other two algorithms at different output flow rates, with an average of 0.23%. The average steady-state time of adjusting the pH value of liquid fertilizer from 7.3 to 6.8 was 72 s, which was superior to the 145 s and 3.2% of fuzzy-PID and 130 s and 1.4% of the Smith controller.