PSO-Fuzzy-IMC算法在充填浓度控制中的应用研究

尾砂充填是一个复杂工业过程，充填过程中存在大滞后、非线性和时变性特点，传统控制策略效果不佳，难以实现尾砂浓度精准控制，因此需要先进控制算法进行充填浓度的精准控制，提高浓度控制的稳定性。以某黄金矿山生产工艺为研究对象，建立充填浓度控制模型，提出了一种模糊内模控制策略，利用粒子群算法对模糊自适应参数进行在线辨识，在MATLAB中进行浓度控制系统仿真。与IMC算法和Fuzzy-IMC算法对比，优化后的模糊内模控制算法具有超调量小、鲁棒性高等优点，浓度控制响应速度快，稳定性高，在抗干扰性和稳定性方面优于内模控制和模糊内模控制算法，浓度控制误差在2%，比内模控制算法提高3%，明显提高系统的控制精度，更好地满足实际应用的要求。

Application of PSO-Fuzzy-IMC algorithm in filling concentration control

The tailings filling is a complex industrial process, which has the characteristics of large time lag, nonlinear and time variability, the traditional control strategy is not effective and it is difficult to achieve accurate control of concentration, therefore, the advanced control algorithm is needed to control the filling concentration accurately and improve the stability of concentration control.The concentration control model is established based on the production process of a gold mineas as the research object, a fuzzy internal model control strategy is proposed, the PSO algorithm is used to identify the fuzzy adaptive parameters online,the concentration control system is simulated in MATLAB.Compared with IMC algorithm and fuzzy IMC algorithm, the optimized fuzzy internal model control algorithm has the advantages of small overshoot, high robustness, the concentration control has fast response speed and high stability, it is superior to IMC and Fuzzy-IMC algorithm in anti-interference and stability, the concentration control error is 2%, which is 3% higher than IMC algorithm, it can significantly improve the control precision of the system and better meet the requirements of practical applications.