论文标题
增强的轮廓跟踪：一种基于时变的内部模型原理方法
Enhanced Contour Tracking: a Time-Varying Internal Model Principle-Based Approach
论文作者
论文摘要
轮廓跟踪在多轴运动控制系统中起着至关重要的作用，并且需要在每个轴上进行多轴轮廓和标准伺服性能。在现有的轮廓控制方法中，交叉耦合控制（CCC）缺乏通用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，并且设计不适合多轴轮廓跟踪。在这里，我们提出了一种新型的基于时变的内部模型原理轮廓控制（TV-IMCC）方法，以通过轴向和轮廓误差减少来增强轮廓跟踪性能。所提出的TV-IMCC是双重的，包括带有用于轮廓调节的主奴隶结构的扩展位置域框架，以及每个轴向跟踪精度改进的时间变化的内部模型原理控制器。具体而言，提出了一种新型的信号转换算法，该算法是使用扩展位置域框架提出的，因此可以将原始的N轴轮廓问题解耦到（N-1）位置域中的两轴两轴主奴隶跟踪问题，并且也可以将候选者的轮廓类别分类。因此，提出了基于时间变化的内部模型原理控制方法来处理轴向系统中的时间变化动力学，这是由于时间和位置域之间的转换而产生的。此外，为TV-IMCC的闭环系统提供了稳定性分析。与现有方法相比，各种模拟和实验结果通过增强的轮廓跟踪性能验证了TV-IMCC。此外，对主轴的精度没有严格的要求，因此TV-IMCC的潜在应用是多轴宏观微运动系统。
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.
