Research On Temperature Control Method For Small Greenhouse Based On MPC

The intelligence of greenhouse is a representative application of modern agriculture.Greenhouse can overcome the differences in season and region,and provide suitable temperature during the non-growing season or climate.However,greenhouse is a complex system that is susceptible to various environmental factors,and has characteristics such as time-varying,instability,and strong inertia.These difficulties make it difficult to obtain satisfactory control effects using traditional control methods.Therefore,this thesis proposes a moving horizon estimation MPC control method,which achieves stable,efficient,and precise control of greenhouse temperature.The main work of this thesis is as follows:(1)Multiple methods were used to establish a transient heat transfer model of the greenhouse.A small-scale experimental environment of greenhouse was built,and a large amount of real-time temperature control data of the actual greenhouse environment was collected and analyzed.Based on the measured temperature control data in the real experimental environment,FOPDT,SOPDT,and physical models were used to establish the temperature control model,and the optimal model was selected based on the identification effect.The results showed that the identification effect of the physical model was the best,with Lowest identification error.Then,three sets of data with completely different voltage input strategies were selected to further test and verify the robustness of the physical model.The results showed that the fitting error of the three sets of data was within 5%.(2)By establishing a transient heat transfer model of the greenhouse,a simulation experiment of temperature control was conducted using conventional PID control method,and the control effect was analyzed.The results showed that the performance of the traditional PID control method was relatively stable under steady-state conditions,but there were problems such as slow response speed and large overshoot.(3)In this study,conventional MPC control method and fuzzy logic MPC control method were used to overcome the limitations of PID controller.To further improve the stability and adaptability,a moving horizon estimation MPC control method is proposed.The moving horizon estimation MPC control method can update the parameters of the prediction model more timely with the change of environmental factors to ensure the accuracy of model prediction.Simulation data showed that compared with the fuzzy logic MPC control method,the moving horizon estimation MPC control algorithm had better control effect under different environmental parameters,further shortened the control time,reduced overshoot,and had smaller steady-state error.(4)In the actual greenhouse environment,temperature control experiments were conducted using conventional PID control method,conventional MPC control method,fuzzy logic MPC control method,and moving horizon estimation MPC control method,with a given target temperature.The temperature control effects were compared,and a 24-hour temperature control experiment was conducted on the moving horizon estimation MPC controller to observe the long-term robustness of the system.The results showed that the moving horizon estimation MPC control system could achieve intelligent temperature control and achieve excellent temperature control effect.