不确定受扰电液伺服系统智能自学习PID控制
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作者单位:

青岛科技大学

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中图分类号:

TP273

基金项目:

青岛市自主创新重大专项(21-1-2-14-zhz),山东省重点扶持区域引进急需紧缺人才项目(鲁发改重大 办[2019]391号),国家自然科学基金项目 (61873139), 山东省自然科学基金项目(ZR2017MEE071) 资助.


Intelligent self-learning PID control of electro-hydraulic servo system with uncertain disturbances
Author:
Affiliation:

Qingdao University of Science and Technology

Fund Project:

Supported by the Independent Innovation Major Project of Qingdao (21-1-2-14-zhz) and Shortage Talents Program in Key Supporting Regions of Shandong Province (Major Office of Shandong Development and Reform Commission [2019]391) and the National Natural Science Foundation of China (61873139) and the National Natural Science Foundation of Shandong Province (ZR2017MEE071).

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    摘要:

    本文针对具有参数不确定和外负载扰动的不确定受扰电液伺服系统,提出了一种智能自学习PID控制策略.该方法不依赖于系统的精确模型,是一种数据驱动的控制方法.首先,通过改进的动态线性化方法将非线性非仿射的电液伺服系统等效为含有时变参数项和非线性不确定项的线性仿射形式;然后,分别采用梯度估计算法和时间差分算法对时变参数项和非线性不确定项进行估计;进而,利用iPID控制引入附加误差信息对过度线性化丢失的信息进行补偿;最后,根据最优准则,设计不确定受扰电液伺服系统的参数更新律和学习控制律.本文通过理论分析与仿真实验验证了该控制策略的收敛性,并通过对比实验,验证了该控制方案应用于电液伺服系统的优越性和精确性.该控制方法抑制了非线性扰动对系统造成的不良影响,并能实现理想轨迹的精确跟踪.

    Abstract:

    This paper explores an intelligent self-learning PID control strategy for uncertain disturbed electro-hydraulic servo system with parameter uncertainty and external load disturbance. This method is a data-driven control strategy that independent of the precise model of the system. Firstly, the linear affine electro-hydraulic servo system with time-varying parameter term and nonlinear uncertainty term is devised by an improved dynamic linearization method. Then, the gradient estimation method and the time difference method are utilized to estimate the time-varying parameter term and nonlinear uncertainty term respectively. Furthermore, the lost information of over-linearization is compensated by additional error information from iPID. Finally, the parameter updating law and learning control law of the electro-hydraulic servo system are designed according to optimal criteria. The convergence of control strategy is proved by theoretical analysis and simulation experiments. And the superiority and accuracy of the method are verified by comparative experiments. The paper shows that the adverse effect of nonlinear disturbance is suppressed and the accurate tracking of ideal trajectory is realized.

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  • 收稿日期:2021-06-08
  • 最后修改日期:2021-11-26
  • 录用日期:2021-12-09
  • 在线发布日期: 2022-01-02
  • 出版日期: