粒子群整定模糊PID控制纸机干燥部压力研究

Study on the Pressure Control of the Dryer in Paper Machine with Fuzzy PID Control Optimizing by Particle Swarm

中文关键词:  蒸汽压力  纸机  粒子群算法  模糊控制  PID控制

Key Words:vapor pressure  paper machine  particle swarm optimization  fuzzy control  PID control

中文摘要:

      针对高速纸机烘缸蒸汽压力是一个具有惯性、大延迟特性的控制目标，很难建立精确的数学模型的问题，设计了模糊PID控制器，通过模糊推理对PID的参数在线调整，但由于专家经验具有局限性、盲目性以及模糊控制内不确定因子过多，导致控制器效果无法快速达到稳态，因此，加入粒子群算法对量化因子和比例因子先在离线状态下进行迭代优化后，再通过模糊PID控制器在烘缸蒸汽压力控制系统进行仿真应用。仿真结果表明，采用基于粒子群算法优化的模糊PID控制器比传统的PID控制具有较强的鲁棒性和快速响应，具有明显的优越性。

Abstract:

      Due to the steam pressure of high speed paper machine dryer is a control target with inertia and big delay characteristics, it is very difficult to establish its precise mathematical model, the fuzzy PID controller was designed and the PID parameters were adjusted online by fuzzy reasoning. However, the controller function could not quickly reach the steady state, because of the limitation and blindness of the expert experience as well as too many uncertain factors in fuzzy control, therefore firstly the quantization factor and scaling factor were offline iterative optimized by adding particle swarm optimization algorithm, then simulation application in dryer steam pressure control system through fuzzy PID controller was carried out. The simulation results showed that the fuzzy PID controller based on particle swarm optimization algorithm had stronger robustness and faster response than the traditional PID control, and had obvious superiority.