ACPSO优化模糊PID的木塑复合材料挤出机温度控制研究  

Research on Temperature Control of Wood Plastic Composites Extruder Based on Adaptive Chaos Particle Swarm Optimization Algorithm of Fuzzy PID Control

作　　者：刘凯伟[1] 唐文秀[1] 孙丽萍[1] 王海刚[1] 

机构地区：[1]东北林业大学

出　　处：《林产工业》2016年第12期11-15,42,共6页China Forest Products Industry

基　　金：国家十二五科技支撑计划课题"木塑复合材料挤出制造关键技术研究与示范"(2012BAD32B04)

摘　　要：木塑复合材料挤出机料筒温度控制系统具有纯滞后、大惯性、非线性、时变等特点,其数学模型难以精确建立,采用传统PID控制方法难以达到控制要求。针对此问题,将自适应混沌粒子群优化(ACPSO)的模糊PID控制应用于木塑挤出机料简温度控制,在利用混沌运动的遍历性初始化粒子群后,采用非线性调整机制对惯性权重进行自适应调整,提高整个群体的全局与局部搜索能力,对模糊PID控制器参数K_P、K_I、K_D进行优化,以提升控制效果。仿真结果表明,自适应混沌粒子群优化模糊PID控制在木塑挤出机料筒温度控制中,具有升温速度快、超调量小、调节时间短、抗干扰能力强等优点,极大地提升了料筒温度控制效果。The wood plastic composites extruder barrel temperature control system has the characteristics of pure lag,large inertia,nonlinearity and time variation,its mathematical model is difficult to establish accurately,so traditional PID control method is difficult to achieve control requirements.In order to solve the problem,the algorithm of fuzzy PID control based on adaptive chaotic particle swarm optimization is applied to the extrusion machine barrel temperature control.After the ergodic property of the chaotic motion is used to initialize the particle swarm,the nonlinear adjustment mechanism is used to adjust the inertia weight adaptively,with the improvement of global and local search ability of the whole group and the optimization of quantization factor and Kp,Kp KD,the results show that the control effect is enhanced.The simulation results show that the adaptive chaotic particle swarm optimization algorithm for fuzzy PID control has the advantages of fast heating speed,small overshoot,short adjusting time,strong anti-interference ability in the extruder barrel temperature control of WPC,the effect of barrel temperature control has been greatly improved.

关 键 词：木塑复合材料 自适应混沌粒子群 模糊控制 料筒温度 

分 类 号：TS653[轻工技术与工程] TP391.9[自动化与计算机技术—计算机应用技术]