Proceedings Article | 9 December 2022
KEYWORDS: Atmospheric modeling, Solar radiation models, Device simulation, Mathematical modeling, Control systems, Solar radiation, Thermodynamics, Data modeling, Computer simulations, Sun, Adaptive control, Agriculture
The solar greenhouse is an infrastructure widely used in agricultural production, and the precise control of its temperature can stabilize yield and production quality. To improve the air temperature control performance without affecting the actual production, a method for simulation modeling of the greenhouse and its air temperature control was proposed based on the thermodynamic principle. Firstly, by combining the following main influencing factors: the heat gained from solar radiation, the heat transferred via ventilation, conduction, long-wave radiation, and the heat storaged by wall, a mathematical model of the greenhouse was constructed. Secondly, a classical proportion-integration-differentiation (cPID) controller was deployed for the air temperature control of the greenhouse based on ventilation. Then an enhancement for cPID, a single neuron proportion-integration-differentiation (SNPID) controller was proposed to improve the control effect, and the former cPID controller acted as a comparison. Next, a MATLAB/Simulink simulation was carried out based on the solar greenhouse model and the PID controller models. As the experimental results show, with sunlight input and Gaussian noise interference in the controlled greenhouse model, the maximum positive and negative temperature offset of SNPID are both smaller than the cPID results, and after interference at the simulated time t=3.33 h, the adjustment time of SNPID is shortened by at least 45.0% compared with cPID. The temperature curve under SNPID control is closer to the target and more stable than the curve of cPID. Thus, the accuracy and robustness of control in this greenhouse are improved.
