Abstract
In the process of crop growth, irrational fertilizer application methods have caused waste of fertilizer resources and water, as well as damaged the soil’s structure. To puzzle the above problems out, the research constructs the model of water-fertilizer machine by gathering relevant parameters in the field. Considering the system’s plenty of defects and combining it with the MATLAB/simulink system, such as non-linearity, time-varying, large inertia, uncertain mathematical model and severe lag, a fuzzy proportional integral differential control based on particle swarm optimization is proposed in this paper for water and fertilizer integration system. Primarily, the research is done for precision fertilization control of fertilizer integration system and water, and the parameters of fuzzy proportional integral differential gain that schedules controllers are optimized through a particle swarm algorithm. The effectiveness of the suggested controller has been validated by comparing with the control algorithms (proportional integral differential control, fuzzy proportional integral differential control) commonly applied in current fertilizer application systems. Simulation experiments for this research are devised through MATLAB/Simulink simulation platform. Significant improvement in the system’s tuning capabilities by incorporating particle swarm algorithm in the hysteretic non-linear system. Eventually, four control algorithms are experimentally validated in this research at different pH values through Experiments čáre designed in the experimental field. The outcomes demonstrate that the control algorithm in this paper possesses better regulation effect, smaller overshoot, excellent stability and more inadequate rising steady state time compared with the previous controls, which can enables precise control of the fertiliser system.
Highlights
Fertiliser’s rational application is crucial to crops’ growth[1]
On the basis of the ordinary fuzzy PID control model, a particle swarm optimised objective function with time weights is added to the target loss function and I, D and the three parameters P are set as the Ki, Kd and three position variables Kp
The test is carried out to track the accuracy of fertiliser application’s pH control by conventional PID control, fuzzy PID control and fuzzy PID based on particle swarm optimization (PSO)
Summary
Fertiliser’s rational application is crucial to crops’ growth[1]. The amount of fertilizer applied around the world is increasing but is not proportional to the increase in crop yields. The first portion analyzes the pH regulation procedure and establishes the corresponding mathematical model through the equilibrium equation; the second portion constructs the PID control, Fuzzy-PID control and the control proposed in this article respectively, selects the sort of affiliation function, the definition of the thesis domain and the creation of fuzzy rules, and in a similar way supplies implementation operation of the PSO algorithm ; the third portion calculates selection of the relevant parameters, the comparison analysis of the three this research works a validation examination based on the intelligent fertilization system out, and the examination outcomes lead to the conclusion section in following portion of this article. Most of the control objects in industrial production are non-linear, with hysteresis links, high order or even time-varying, making it extremely difficult to establish a fine mathematical control model, traditional PID is difficult to track the ideal target and the effect is inadequate. The affiliation value of two fuzzy subsets’ intersection is generally taken as 0.2-0.7, which can make the system more sensitive and more stable
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