粉状食品计量控制系统设计

Design of Powder Food Measurement Control System

粉状食品在包装计量过程中由于系统振动、传感器信号波动及螺杆的旋转惯性等因素的影响,使得粉状食品在计量过程中存在时滞性、非线性等特点,为克服时滞性和非线性对计量精度的影响,设计一种基于模糊神经网络PID的粉状食品计量控制系统。介绍传统的粉状计量PID控制方法,为提高传统PID控制系统的自适应能力,在传统PID控制系统中引入模糊控制和神经网络控制,利用模糊神经网络实现PID中比例、积分、微分3个参数的自适应调整。仿真结果表明,模糊神经网络PID控制方法相比于传统PID控制具有更高的控制精度,超调量更小,能够在更短时间内实现控制量的收敛。

Due to the influence of system vibration, sensor signal fluctuation and screw rotation inertia in the process of powder food packaging measurement, there are time-delay and nonlinear characteristics in the measurement process of powdery food. In order to overcome the influence of time delay and nonlinearity on measurement accuracy, a powder food metering control system based on Fuzzy Neural Network PID is designed. In order to improve the self-adaptive ability of the traditional PID control system, fuzzy control and neural network control are introduced into the traditional PID control system. The fuzzy neural network is used to realize the self-adaptive adjustment of the proportion, integral and differential parameters in PID. The simulation results show that compared with the traditional PID control, the fuzzy neural network PID control method has higher control precision, smaller overshoot, and can achieve the convergence of control quantity in a shorter time.