Multi-objective Optimization Control of Flotation Process Based on Policy Iteration

This paper proposes a data-driven, multi-objective optimization control method based on policy iteration for flotation process, addressing the limitations of existing control methods that rely on the system model and cannot satisfy multiple performance indices simultaneously. Firstly, The ordinary linear quadratic regulator algorithm is improved with process data, enabling the algorithm to obtain optimal feedback gain without relying on the internal dynamics model of the system. Then, This method is further extended to the situation where multiple objectives exist, minimizing the deviation of the final additive amount while meeting control requirements for both concentrate and tailings grade. Finally, the convergence and effectiveness of the proposed method are verified by simulation experiments.