雕刻机系统数据驱动建模与容错跟踪控制
作者:
作者单位:

中国矿业大学

作者简介:

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中图分类号:

TP273

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Data-driven Modelling and Fault-tolerant Tracking Control for Engraving Machine Systems
Author:
Affiliation:

China University of Mining and Technology

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    通过分析在速度控制运行模式的雕刻机系统输入角速度和输出位置之间的机理关系,将其系统利用一个积分因子和一个稳定传递函数相连接的模型进行模拟。通过引入微分滤波器对采样数据进行处理,将难以辨识的临界不稳定积分模型转换成易于辨识的稳定模型。本文提出了一种能够精确估计带积分因子的递推最小二乘算法。并采用辅助变量法消除因滤波引起的有色噪声的影响。所提算法可以确保在开环状态下对积分系统进行精确估计。对于多轴雕刻机运动控制系统,提出了一种基于中间观测器的容错跟踪控制算法。针对与输入通道匹配的过程故障,设计基于故障估计值的容错控制反馈率进行有效补偿。对于不匹配故障,通过调节调节中间观测器增益实现充分抑制。最后,通过和现有算法对比,实验验证了所提出算法的可行性和优越性。

    Abstract:

    By analyzing the mechanism relationship between the input angular velocity and the output position of the engraving machine system in speed control mode, the system is simulated as a model connected by an integrating factor and a stable transfer function. By introducing a differential filter to process the sampling data, the critical unstable integrating model is transformed into a stable model which is easy to identify. This paper proposes a recursive least squares algorithm which can accurately estimate the model with integrating factor. Besides, the instrumental variables method is applied to eliminate the influence of colored noise caused by filtering. The proposed algorithm can ensure the accurate estimation of the integrating system in open loop state. A fault-tolerant tracking control algorithm based on intermediate observer is proposed for multi-axis engraving machine motion control system. Aiming at the process fault matching with the input channel, a fault-tolerant control feedback rate based on fault estimation value is designed to effectively compensate. For the mismatched fault, it can be fully suppressed by adjusting intermediate observer gain. Finally, compared with the existing algorithm, the feasibility and superiority of the proposed algorithm are verified by experiment tests.

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历史
  • 收稿日期:2021-12-15
  • 最后修改日期:2022-11-24
  • 录用日期:2022-04-15
  • 在线发布日期: 2022-05-02
  • 出版日期: