基于神经网络的流涎机组多电机同步控制研究

针对流涎薄膜生产机组多电机同步控制系统的非线性、时变、容易受负载扰动等特性，提出了基于神经网络PID控制器与偏差耦合控制结构相结合的多电机同步控制策略，设计了神经网络PID控制器，并进行了仿真和实验。结果表明：该控制算法稳定性能高、鲁棒性能好、收敛速度快，能够有效克服外部扰动和参数变化带来的同步误差，相对于传统的同步控制方案能够更好地实现流涎机组的多电机同步控制。

Research on Multi-motor Synchronization of Salivation Unit Based on Neural Network

According to the salivation unit's multi-motor synchronous control system of nonlinear, time varying, load disturbance and other vulnerable features, neural network PID controllers were designed and a strategy of realtive coupling control for multi-motor synchronization based on neural network PID contorl was proposed;Simulation results show that: the control algorithm has a good stability behavior and robust performance ,a quick convergence rate and can achieve the multi-motor synchronous control of salivation unit effectively compared with the traditional control strategy.