文章摘要
陈家俊,贺云波.伺服系统中PID控制器参数整定的研究[J].机床与液压,2021,49(1):13-16.
CHEN Jiajun,HE Yunbo.Study on Parameter Tuning for PID Controller in Servo System[J].Machine Tool & Hydraulics,2021,49(1):13-16
伺服系统中PID控制器参数整定的研究
Study on Parameter Tuning for PID Controller in Servo System
  
DOI:10.3969/j.issn.1001-3881.2021.01.003
中文关键词: 机器学习  模糊控制  BP算法  PID参数整定
英文关键词: Machine learning  Fuzzy control  BP algorithm  PID parameters tuning
基金项目:国家自然科学基金面上项目(51675106);国家自然科学基金联合基金项目(U1601202);广东省自然科学基金(2016A030308016;2015A030312008);广东省R&D重点项目(2015B010133005;2015B010104006;2015B0101040088);广东省重大研发专项(2018B090906002)
作者单位E-mail
陈家俊 广东工业大学省部共建精密电子制造技术与装备国家重点实验室 523321170@qq.com 
贺云波 广东工业大学省部共建精密电子制造技术与装备国家重点实验室 heyunbo@gdut.edu.cn 
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中文摘要:
      针对伺服系统中常用的比例-积分-微分(PID)控制器的参数手动整定不方便的问题,对机器学习算法和模糊控制进行研究,重点分析反向传播(BP)算法和模糊控制器的设计方法,提出一种基于机器学习和模糊控制的PID参数整定方法。利用BP神经网络的学习能力得到系统模型,结合模糊控制进行预测得到PID参数,并在实验平台上进行验证。研究结果表明:通过机器学习和模糊控制得到的PID参数具有较好的控制效果,该方法能够避免手动整定PID参数,节省大量时间。
英文摘要:
      Aimed at the inconvenience of manual tuning parameters of PID controller commonly used in servo system, machine learning algorithm and fuzzy control were researched. The back propagation (BP) algorithm and design methods of fuzzy controller were emphatically analyzed. A PID parameter tuning method based on machine learning algorithm and fuzzy control was proposed. The learning ability of BP neural network was used to get the system model, and the PID parameters were predicted by combining with the fuzzy control, which were verified on the experimental platform. The results indicate that the PID parameters obtained by using machine learning and fuzzy control have better control effect. By using this method, it can avoid manual tuning of PID parameters and save a lot of time.
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