Green Grain Storage Mechanical Aeration Process Model Predictive Control Study

Mechanical aeration is a key technology to realize green and ecology grain storage. With the social progress, improvement of living standards and the increasingly rigorous issue of food security, higher requirements such as grain security,quality preservation and energy-saving storage were put forward to stored grain mechanical aeration technology. Traditional methods aiming at meeting the above requirements were usually to optimize the aeration process with improvement of the bin, devices, aeration system structure and process design. However, stored grain aeration process control study was relatively insufficient. Thus, this dissertation aimed at studies of basic theory and application of mechanical aeration process control methods and presented the control methods for mechanical aeration which could not only control the grain moisture content and temperature at the safe level, but also optimize grain quality and energy consumption, and finally realize the green grain storage aims such as safe and energy saving storage, as well as grain quality preservation.The main contents were shown as follows:1.Development of stored grain aeration control study platform.Design requirements of the stored grain aeration control study platform were introduced and the platform was developed according to stored grain system characteristics together with measurement and control theory. Working principles of the platform were analyzed from the viewpoint of system functions and the platform structure was introduced in detail in terms of hardware and software. Finally, many experiments were carried out to test the platform and the results showed that the platform could meet the requirements of aeration control study and proved to be a reliable platform for studies in this dissertation.2.Mathematical modeling of the mass and heat transfer for stored grain aeration processAccording to the mass and heat transfer mechanism during stored grain aeration,a partial differential equation model was developed. The finite difference method was used to solve the model in Matlab and the temperature and moisture distributions in grain bulk were simulated during aeration. An experiment was carried out and results showed that the model could achieve good simulation accuracy. Finally, application of the model such as stored grain aeration time calculation, process control method simulation and model prediction control were analyzed.3.Stored grain aeration process lumped parameter model predictive control methodFor grain bulk with evenly distributed heat and moisture parameters, the stored grain aeration control problem was converted to multi-variable coupling control problem and a novel stored grain aeration process lumped parameter model predictive control method was introduced. An optimization objective function relevant to grain moisture content, grain temperature, grain quality and system energy consumption was developed and the particle swarm optimization (PSO) algorithm was used to solve the objective function in order to control grain temperature and moisture content and optimize grain quality and energy consumption, and finally realize green grain storage. Simulation was conducted and results showed that the control method could be used to control grain temperature and moisture content and save energy.Experiment was carried out and results show that control method is efficient and effective. Finally, the application of the control method was analyzed.4.Stored grain aeration process distributed parameter model predictive control methodThe stored grain aeration process distributed parameter model predictive method was studied and the control problems of heat and moisture parameters with significant distribution characteristics were converted to multiple model control problem. The objective function relevant to grain moisture content,grain temperature,grain quality and energy consumption and a model shifting strategy were presented. PSO algorithm was also used to solve the objective function to realize the grain temperature and moisture content control and make them distribute evenly together with grain quality optimization and energy consumption, and finally realize green grain storage.Simulation with the control method was conducted and results showed that the control method could be used to control and uniform grain temperature and moisture content effectively and save energy. Experiment was carried out and results showed that the control method is effective. Finally the control method application was analyzed.