Research On Nonlinear Model Predictive Control Algorithm For Hydrometallurgy Leaching Process

Mineral resources are the basis of economic and social development,and play an important role in the development of economic and social.Sustainable economic development is inseparable from the supply of mineral resources.In our country,mineral resources are rich and variety,but it is in the process of rapid economic development and has large populations,which leads to large demand for mineral resources.Therefore,it is of great significance to improve the utilization of mineral resources to ensure the sustainable development of the country.As an important metallurgy technology,the significant advantages of hydrometallurgy are high comprehensive recovery rates of valuable metals in raw materials,benefit for environmental protection,and easy fulfillment of continuous and automated production processes.Therefore,hydrometallurgy is more suitable for recovering metal resources.Leaching process is one of the central unit operations in the hydrometallurgical processes.In this thesis,complete dynamic mechanistic models are established based on analyzing the characteristics of the leaching process for a gold smelter.Then comprehensive research on hydrometallurgy leaching process is developed.This thesis proposes a nonlinear predictive control method based on global orthogonal collocation method on the basis of the mechanism model.The main researches are summarized as follows:1.After the detail analysis of the reaction mechanism of the leaching process,the dynamic mechanistic models of gold cyanidation leaching process are established based on the mass conservation equations of gold in the ore,gold in the liquid and cyanide ion in the liquid,as well as the corresponding kinetic reaction rate models of gold and cyanide ion.Moreover,the dynamic response of the leaching process can be got by simulation based on the above model,and the effect of key variables on the leaching rate is analyzed by the simulation,which validate the rationality of the mechanism model.2.Traditional predictive control methods for nonlinear processes firstly linearize prediction model and then implement control.This method is suitable for weak nonlinear control systems but has poor control performance for strong nonlinear processes.Leaching process is a relatively complex nonlinear process and linearization may cause loss of some important features.So a nonlinear predictive control method based on global orthogonal collocation method is presented in this thesis to solve optimal control problem.3.The control performances of the proposal nonlinear predictive control method,including tracking performance,disturbance rejection and model-plant mismatch robustness,are compared with the traditional linear predictive control method.The nonlinear predictive control method proposed in this thesis has advantages of smaller overshoot,faster response,higher stability and stronger robustness when model mismatch.