Design of MFAC greenhouse temperature controller based on LESO with disturbance estimation and fuzzy controller with parameter tuning

Abstract

Abstract The proper temperature is essential for the growth and development of greenhouse crops. Therefore, it is necessary to determine an appropriate greenhouse temperature automatic control strategy. In this paper, a model-free adaptive greenhouse temperature control strategy is proposed by combining a linear extended state observer and a fuzzy controller. Specifically, the linear extended state observer is introduced to estimate model approximation error generated by pseudo gradient estimation. The fuzzy controller is used to correct the system parameter ρ online. The simulation results show that when there is no disturbance, compared with the typical model-free adaptive scheme, the MAE and RMSE of the greenhouse temperature control scheme proposed in this paper are reduced by 57.55% and 5.40% respectively. In the presence of custom disturbances, the proposed control scheme still has a faster response speed, stronger robustness, and higher control accuracy. And the proposed method can reduce the frequent action of the actuator, thus effectively reducing the energy cost.