Application of Nonlinear Model Predictive Control Method Based on GA for Northeastern Greenhouse in China

The purpose of the greenhouse system is to build a suitable microclimate environment for crop growth in northeastern China. The precise control of environmental factors is the key factor to ensure the high quality of crop growth. However, the actual greenhouse system is described as a complex dynamic characteristic with strong nonlinear, strong coupling, multiple disturbances. Therefore, the traditional PID control method is difficult to solve the above problems. In order to solve the above problems, this paper develops a microclimate dynamic model suitable for the northeastern greenhouse. Subsequently, the Nonlinear Model Predictive Control (NMPC) algorithm combines with GA algorithm is applied to the northeastern greenhouse. This scheme is applied to the control of temperature, humidity and carbon dioxide concentration in the greenhouse compared with the traditional PID control. The simulation results show that the nonlinear model predictive control based on GA algorithm has better control performance and stability. Furthermore, the proposed method can meet the actual demand.