基于神经网络算法的工缝机节能电动机控制系统的设计  

Design of industrial sewing control system of energy-saving motor based on DSP

作　　者：徐展鹏[1] 孙云云[1,2] 刘涵[1,2] 郭吉丰[1,2] 

机构地区：[1]浙江大学电气工程学院,浙江杭州310027 [2]浙江省现代纺织工业研究院,浙江绍兴310030

出　　处：《纺织学报》2011年第12期128-133,共6页Journal of Textile Research

摘　　要：为解决目前纺织业工缝设备大量运用的离合式异步电动机造成能源利用效率低下的问题,设计了一种基于DSP芯片的节能电动机控制系统。由于工业平缝机是一个滞后、非线性、变参数的控制系统,采用传统的PID控制,因其参数不能随着受控系统的变化进行在线调节,会使控制的有效性与可靠性下降。针对这一缺陷,在传统的PID基础上加入了BP神经网络算法,利用其自学习和自调节能力实现了PID参数随系统变化进行自行调节.利用BP网络PID的原理,对调速系统进行了MatLab仿真,证明了BP网络PID优于传统PID的控制能力。最后将这一结果运用于实际的软件设计中,取得了预期的效果。In order to address the problem of low electric efficiency of clutch asynchronous motors used abundantly in the industrial sewing machine control systems,an energy saving motor control system based on the DSP was designed.The industrial sewing machine control system is hysteretic,time-variant and nonlinear,hence the conventional PID control algorithm will reduce the serviceability and reliability of the system because the PID parameters cannot be adjusted timely when the controlled objects are varying.Considering this phenomenon,BP neural algorithm is added to the conventional PID control algorithm,whose self-learning and self-adjusting capabilities help realize the thoughts that parameters of a PID controller can regulate themselves as the system is varying.Furthermore,applying the BP-PID algorithm,MatLab simulations of the energy saving motor control system are conducted,and the results of the simulations demonstrate that the control performance of BP-PID is more super than that of conventional PID.Lastly,the BP algorithm is synthesized in the software design,and achieves a satisfactory result.

关 键 词：异步电动机 节能电动机 传统PID BP神经网络 

分 类 号：TS941.562[轻工技术与工程—服装设计与工程]