基于改进的PSO算法在纸机干燥部压力控制PID参数整定中的应用  

Application of Improved PSO Algorithm in Parameter Setting of Pressure Control in Paper Drying

作　　者：李茜[1] 庞肖 汤伟[1] 王孟效 

机构地区：[1]陕西科技大学电气与信息工程学院,陕西西安710021 [2]陕西西微测控工程有限公司,陕西咸阳712081

出　　处：《纸和造纸》2016年第10期4-6,共3页Paper and Paper Making

摘　　要：纸机干燥部的蒸汽压力控制直接影响蒸汽消耗量以及纸张的质量,针对干燥部的工况多变,选用传统PID不易控制,标准粒子群算法寻优精度不高、易导致早熟现象等缺陷,提出一种改进的粒子群算法来自整定PID参数,通过引入线性递减的惯性权重ω来协调PSO的全局和局部寻优能力。MATLAB仿真实验表明,采用改进的粒子群算法整定后的干燥部压力控制PID有更好的鲁棒性和响应速度。Drying section of paper machine pressure control directly affect the steam consumption and paper quality, for drying conditions changing, use the traditional PID control, the standard particle swarm algorithm to find optimal precision is not high, easy to cause premature phenomena such as defects, put forward a kind of improved particle swarm optimization algorithm from tuning PID parameters, by introducing the linear decreasing inertia weight ~ to coordinate the PSO＇s global and local searching ability. MATLAB simulation results show that the improved particle swarm optimization algorithm has better robustness and response speed of the pressure control PID after the whole set.

关 键 词：干燥部压力 粒子群算法 PID参数自整定 MATLAB仿真 

分 类 号：TS734[轻工技术与工程—制浆造纸工程]