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Steady State Frequency Response Design of Finite Time Iterative Learning Control
The Journal of the Astronautical Sciences ( IF 1.2 ) Pub Date : 2019-12-18 , DOI: 10.1007/s40295-019-00198-9
Benjamas Panomruttanarug , Richard W. Longman , Minh Q. Phan

Steady state frequency response is a major design approach in control theory, and is normally used to obtain reasonable response to commands up to a chosen or obtainable bandwidth. By contrast, iterative learning control (ILC) aims to converge to zero error at all time steps of a finite time tracking task, using an iterative update of the command to a control system. It asks for zero error during the transient as well as steady state response phases. This paper develops a rigorous design approach to apply frequency response to the ILC problem. The gains in an FIR compensator from repetitive control are used to fill the ILC learning gain matrix. The compensator mimics the inverse frequency response. This paper does not ask for zero error for one or more initial times steps, in oder to address a well posed problem that is not trying to converge to an unstable command input. It is seen that by adjusting just one gain in the upper left corner of the learning matrix, the ILC can be stabilized in spite of the length of time involving transients. This makes a very simple design process. One can also adjust two gains in the first row, or better a two-by-two block, but further adjustment seems of limited benefit. The frequency based ILC design developed here is compared to existing ILC design methods, and shown to be vastly superior in convergence rate. It also has the advantage that the ILC can be designed directly from frequency response test data without creating a mathematical model.

中文翻译:

有限时间迭代学习控制的稳态频率响应设计

稳态频率响应是控制理论中的一种主要设计方法,通常用于获得对选定或可获得带宽的命令的合理响应。相比之下,迭代学习控制(ILC)的目标是使用对控制系统的命令迭代更新,在有限时间跟踪任务的所有时间步长收敛到零误差。它要求在瞬态以及稳态响应阶段均实现零误差。本文开发了一种严格的设计方法,可将频率响应应用于ILC问题。FIR补偿器中来自重复控制的增益用于填充ILC学习增益矩阵。补偿器模拟反向频率响应。本文不针对一个或多个初始时间步长要求零误差,更好地解决了未试图收敛到不稳定命令输入的恰当问题。可以看出,通过调整学习矩阵左上角的一个增益,尽管涉及瞬变的时间长短,ILC仍可以稳定下来。这使得设计过程非常简单。一个人也可以在第一行中调整两个增益,或者更好地在一个2乘2的块中调整,但是进一步的调整似乎没有什么好处。将此处开发的基于频率的ILC设计与现有的ILC设计方法进行了比较,并显示出收敛速度方面的优越性。它还具有可以直接从频率响应测试数据设计ILC的优势,而无需创建数学模型。尽管涉及瞬变的时间很长,但ILC还是可以稳定的。这使得设计过程非常简单。一个人也可以在第一行中调整两个增益,或者更好地在一个2乘2的块中调整,但是进一步的调整似乎没有什么好处。将此处开发的基于频率的ILC设计与现有的ILC设计方法进行了比较,并显示出收敛速度方面的优越性。它还具有可以直接从频率响应测试数据设计ILC的优势,而无需创建数学模型。尽管涉及瞬变的时间很长,但ILC还是可以稳定的。这使得设计过程非常简单。一个人也可以在第一行中调整两个增益,或者更好地是一个2乘2的块,但是进一步的调整似乎没有什么好处。将此处开发的基于频率的ILC设计与现有的ILC设计方法进行了比较,并显示出收敛速度方面的优越性。它还具有可以直接从频率响应测试数据设计ILC的优势,而无需创建数学模型。并且在收敛速度方面显示出极大的优势。它还具有可以直接从频率响应测试数据设计ILC的优势,而无需创建数学模型。并且在收敛速度方面显示出极大的优势。它还具有可以直接从频率响应测试数据设计ILC的优势,而无需创建数学模型。
更新日期:2019-12-18
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