基于模糊神经网络的双卷扬同步控制技术研究

Research on Synchronous Control Technology for Double Hoist Based on Fuzzy Neural Network

利用模糊推理功能和神经网络的自学习功能对PID控制参数进行调节,可以有效解决传统PID控制参数无法在线整定的问题。针对液压同步控制特点,本研究把模糊神经PID控制应用于重型起重机单钩双卷扬系统,利用主从控制方法,完成从动马达对主动马达的跟踪控制,使两个马达的转速趋于一致。仿真与实验结果表明,所用方法可以大幅减小同步误差的幅度,有效解决双卷扬同步系统中存在的误差较大问题,将误差控制在允许范围内,控制精度高,鲁棒性能好,具有一定的实际应用价值。

Using fuzzy reasoning and neural network self-learning function of PID control parameters to adjust, it can effectively solve the traditional PID control parameters which can＇t online set problems. According to the characteristics of hydraulic synchronous control of this was to apply fuzzy neural PID control to crane hook double winding system, it uses the master-slave control method, completes the tracking control of the active motor driven motor, makes the speed of the two motors tend to be more consistena Simulation and experimental results show that the method can greatly reduce the synchronization error margin, effectively solve the double winding synchronous system, and the error is the bigger problems in the range of allowable error control at, high control precision, good robust performance, and has certain actual application value.