增强的轮廓跟踪：基于时间变化内部模型原理的方法
Enhanced Contour Tracking: a Time-Varying Internal Model Principle-Based Approach
AI总结：
本文提出了一种基于时间变化内部模型原理的新型轮廓跟踪控制方法，通过扩展位置域框架和信号转换算法，提升多轴轮廓跟踪性能并减少误差。
摘要：
轮廓跟踪在多轴运动控制系统中起着关键作用，它要求具有多轴轮廓跟踪以及每个轴的标准伺服性能。在现有的轮廓跟踪控制方法中，交叉耦合控制（CCC）缺乏对一般轮廓的渐近跟踪性能，而任务坐标框架（TCF）控制通常会导致系统非线性，并且由于设计原因不适用于多轴轮廓跟踪。本文提出了一种新的基于时间变化内部模型原理的轮廓跟踪控制（TV-IMCC）方法，以增强轮廓跟踪性能，同时减少轴向和轮廓误差。所提出的TV-IMCC是双重的，包括带有主从结构的扩展位置域框架用于轮廓调节，以及基于时间变化内部模型原理的每个轴跟踪精度改进控制器。具体而言，提出了一种新的信号转换算法，通过扩展的位置域框架，原始的n轴轮廓跟踪问题可以分解为位置域中的（n-1）两个轴主从跟踪问题，并且轮廓候选类别也可以扩展。借此，提出了一种基于时间变化内部模型原理的控制方法，以处理由于时间和位置域之间转换而产生的轴向系统的时间变化动态。此外，为TV-IMCC闭环系统的稳定性分析提供了证明。各种仿真和实验结果验证了TV-IMCC在对比现有方法时具有增强的轮廓跟踪性能。此外，主轴的精度没有严格要求，因此TV-IMCC的一个潜在应用是多轴宏微运动系统。
英文摘要：
Contour tracking plays a crucial role in multi-axis motion control systems, and it requires both multi-axial contouring as well as standard servo performance in each axis. Among the existing contouring control methods, the cross coupled control (CCC) lacks of an asymptotical tracking performance for general contours, and the task coordinate frame (TCF) control usually leads to system nonlinearity, and by design is not well-suited for multi-axis contour tracking. Here we propose a novel time-varying internal model principle-based contouring control (TV-IMCC) methodology to enhance contour tracking performance with both axial and contour error reduction. The proposed TV-IMCC is twofold, including an extended position domain framework with master-slave structures for contour regulation, and a time-varying internal model principle-based controller for each axial tracking precision improvement. Specifically, a novel signal conversion algorithm is proposed with the extended position domain framework, hence the original n-axis contouring problem can be decoupled into (n-1) two-axis master-slave tracking problems in the position domain, and the class of contour candidates can be extended as well. With this, the time-varying internal model principle-based control method is proposed to deal with the time-varying dynamics in the axial systems resulted from the transformation between the time and position domains. Furthermore, the stability analysis is provided for the closed-loop system of the TV-IMCC. Various simulation and experimental results validate the TV-IMCC with enhanced contour tracking performance compared with the existing methods. Moreover, there is no strict requirement on the precision of the master axis, therefore a potential application of the TV-IMCC is multi-axis macro-micro motion systems.
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