基于机器学习的机械流水线速度无线控制方法

Wireless Speed Control Method of Machine Pipeline Based on Machine Learning

当前的机械流水线速度控制智能化程度低,对流水线中的意外或者相关情况缺少主动认知学习过程,存在执行速度与期望速度误差大和控制前后速度跟踪误差偏高的问题,提出基于机器学习的机械流水线速度无线控制方法。该方法构采集机械流水线的数据,结合机器学习原理,对采集的机械流水线数据进行主动学习,进而分析机械流水线调节需求的潜在概率,获取认知回归系数,并且根据设计的机械流水线速度控制器,引入认知回归系数至控制器,达到提升机械流水线的速度调节控制智能化程度的目的。实验结果表明:通过测试控制前后速度跟踪误差、速度认知回归观测值误差和机械流水线速度误差,验证了该方法的有效性。

The current mechanical assembly line speed control is low in intelligence,and there is no active cognitive learning process for accidents or related situations.To address the large errors between the execution speed and the expected speed,and reduce the speed tracking errors before and after control,a wireless speed control method for the mechanical pipeline based on machine learning is proposed.Data of the mechanical pipeline is collected and actively learned to analyze the potential probability of the regulation demand of the mechanical pipeline.The cognitive regression coefficient is obtained and introduced to the designed controller so as to improve the intelligence of the speed regulation control of the mechanical pipeline.The experimental results show that the effectiveness of this method is verified by testing the speed tracking error before and after control,the speed cognitive regression observation error and the mechanical pipeline speed error.