Research on improved partial format MFAC greenhouse temperature control method based on low energy consumption optimization.

• Based on the control input cost function of the traditional partial format model-free adaptive control, an effective greenhouse temperature controller is designed by adding an index term that limits energy consumption. • The multi-parameter sensitivity analysis method based on Monte Carlo is used to analyze the sensitivity of the controller parameters to determine which parameters have a greater impact on system performance. Then, the whale optimization algorithm is used to optimize the sensitive controller parameters. This improves the efficiency of parameter tuning. • The improved partial format model-free adaptive controller achieves a balance between control accuracy and low energy consumption. Compared with the traditional partial format model-free adaptive controller, the energy consumption of the improved partial format model-free adaptive controller is reduced by 12.35 %. Temperature is critical to the growth of crops in agricultural greenhouses. Thus, designing a greenhouse temperature controller that maximizes energy savings while maintaining control accuracy is very important. This paper proposes an improved partial format model-free adaptive control method and designs a greenhouse temperature controller based on this method to balance control accuracy and energy consumption. Firstly, a limited energy consumption term is added to the control input cost function of the traditional partial format model-free adaptive control to penalize excessive control input. We derive an improved partial format model-free adaptive control input algorithm and design a greenhouse temperature controller using this algorithm. Then, the controller's sensitive parameters are selected using a Monte Carlo-based parameter sensitivity method. Finally, the whale optimization algorithm is used to optimize the sensitive parameters. The insensitive parameters are set according to experience. This paper, a theoretical study based on simulated experiments, proves the convergent tracking error of the proposed improved partial format model-free adaptive algorithm. Simulation results show that the improved controller minimizes energy consumption while ensuring control accuracy, reducing power consumption by 12.35 % compared to the traditional controller. [ABSTRACT FROM AUTHOR]