基于粒子群算法的球磨机情感智能自适应辨识算法

Emotional Intelligence Adaptive Identification Algorithm for Ball Mill System Based on Particle Swarm Optimization

摘要:

制粉工艺在矿物加工工程技术中极其重要,而球磨机正是其关键设备；针对球磨机系统时变性、非线性的特点,提出了采用大脑情感学习模型(brain emotional learning, BEL)对球磨机系统实现正向模型和逆模型辨识,并利用粒子群算法(PSO)对整个参数空间进行高效并行搜索使参数最优化,并给出球磨机系统数学模型辨识算法；仿真结果表明,改进方法可使模型输出与球磨机系统输出或输入达到一致,具有模型辨识误差小、算法简单的特点。

Abstract:

Milling process is extremely important in mineral processing engineering technology, ball mill is the key equipment.Based on the characteristics of time-varying, nonlinear in ball mill system, proposed use the BEL(Brain Emotional Learning) forward model and inverse model identification of ball mill system, use the PSO parallel search the entire parameter space can efficiently make the parameter optimization, and given mathematical model identification algorithm of ball mill system.The simulation results show that the improved method can make the model output and the ball mill system output or input to achieve consistently,it have the characteristics of model identification error small, the algorithm simple.