Research On Predictive Control Of Aggregate Temperature In Asphalt Mixing Plant

Asphalt mixing plant is the main place of asphalt mixture production.In recent years,with the rapid development of China’s roads,the demand for asphalt mixes is increasing,and at the same time,the quality of the mixes is also subject to higher and higher requirements.In the process of asphalt mixture production,the aggregate temperature is an important parameter affecting the quality of asphalt mixture,therefore,how to ensure that the aggregate temperature meets the requirements of the production process is an important part of asphalt mixture production.At present,asphalt mixing plants generally use PID control method to control the aggregate temperature,however,when a series of uncertainties such as aggregate humidity,ambient temperature and feeding volume change during the production process,it is difficult for PID control method to achieve the ideal temperature control effect.To address the problem of poor PID control,this project investigates the temperature control of asphalt mixing plant aggregates using aggregate heating mechanism,system identification theory,predictive control theory and multi-model control theory,and achieves some meaningful research results.The main research contents of this paper are as follows:1.In this paper,considering the complex physical changes and nonlinear processes of the aggregate temperature system,a four-input one-output aggregate temperature set total parameter model based on energy balance is established based on the internal characteristics of the heating drum and the heat transfer mechanism,and the influence of each input variable on the aggregate temperature is analyzed using this model.Secondly,an asphalt mixing plant aggregate temperature simulation system was established to obtain the real-time simulation data of each input and output variable during its operation,and the unknown parameters in the model were identified by combining with the identification theory.The simulation experimental results show that the obtained model has high accuracy,which lays the foundation for the subsequent predictive control of aggregate temperature based on the model.2.For the characteristics of large inertia,hysteresis and slow time-varying parameters of the aggregate temperature system,the generalized predictive control(GPC)is used to predict the change trend of aggregate outlet temperature and identify the model parameters online,and adjust the control amount of burner throttle opening in advance,so as to achieve the purpose of controlling large inertia,hysteresis and slow time-varying parameters.And for the problems of large computation and possible pathological data in its operation process,the stepped strategy is introduced on the basis of GPC algorithm to improve it,which reduces the computation and improves the speed of the system at the same time,and constrains the fuel control amount to protect the actuator and avoid wear and tear.Finally,it is verified through simulation experiments that the response speed and overshoot of the improved SGPC in aggregate temperature control are better than PID control,with good control performance and robustness.3.In the aggregate heating process,the aggregate feed(load)will occasionally fluctuate greatly with the production requirements,thus causing a large change in the parameters of the aggregate temperature model,when a single model predictive controller is difficult to adapt to such changes,this paper proposes a multi-model switching control strategy,in advance in the aggregate heating system under a number of typical operating conditions,to establish its control mathematical model,and then according to the actual output of the aggregate Then,based on the error between the actual output of the aggregate temperature and each model,the optimal local model is selected as the current prediction model based on the switching performance index at each sampling moment and switched to the controller corresponding to the current model,so as to realize the adaptive control of the aggregate temperature under the full working condition of the load.The simulation results show that the multi-model aggregate temperature prediction control method proposed in this paper is better than PID control,and has good dynamic regulation quality and robustness in a wide range of aggregate load conditions,and can achieve the expected control effect.