Nonlinear Predictive Control Of Underflow Density Of Thickening Process In Hydrometallurgy

With the steady progress of industrialization in our country, it is very important for the sustainable development strategy of our country to use the low grade mineral resources. The remarkable advantages of hydrometallurgy are high comprehensive recovery rates of valuable metals. Therefore it is more suitable to recover low-grade metal resources effectively and economically. Thickening process is an important unit operation which is widely used in hydrometallurgy, the underflow density of it is the key quality index. However, at present, most thickening processes are still in the manual operation state, making its density and flow fluctuate largely and influencing the subsequent production index. The automatic control of thickening process has been a difficult problem due to the harsh working conditions and other factors like the nonlinear and the slow time-varying.In this thesis, with the aim to meet the production index and overcome the nonlinear, the slow time-varying, and the flow fluctuate in underflow density control of the thickening process, and based on the deep insight of the hydrometallurgy procedure, a control strategy of the thickening process was put forward in thesis. The main contents of this thesis are as follows:1. The process of thickening process was introduced combining with the structure characteristics of thicker. The performance of hybrid model of the thickening process was analyzed based on the hybrid model of the thickening process. Finally, the problems and difficulties of underflow density control of thickening process which is the basis for the proposed control approach were obtained.2. Based on the nonlinear, slow time-varying characteristics of thickening process, the predictive functional control method was adopted based on the linearized model, and the hybrid model was linearized and compared with the original mechanism model in this thesis. Then. Through parameters setting and further analysis of the above-described method, predictive functional control method responded quickly but there was some overshoot, which would cause density and flow fluctuant and bring some influence to the process of production.3. In view of the problems that predictive functional control would cause density and flow fluctuant and the characteristics of thickening process, the interior-point quasi-sequential approach was adopted to solve the nonlinear predictive control of underflow density of thickening process in this thesis. Then the method was compared with predictive functional control, we could find that the interior-point quasi-sequential approach nonlinear predictive control has good control effect through simulation analysis, and this method was suitable for the thickening process.4. Semi-physical simulation platform of underflow density predictive control for thickening process was established by taking a thickening section in a hydrometallurgy plant as a research example. The nonlinear predictive control platform of underflow density was accomplished combining with the predictive control theory.