Modifying and optimizing the inverse of the frequency response circulant matrix as an iterative learning control compensator
Shuo Liu, Richard W. Longman

TL;DR
This paper introduces a novel iterative learning control (ILC) design method based on the inverse of the frequency response circulant matrix, enabling faster convergence and improved handling of transients in high-precision tracking tasks.
Contribution
It proposes a frequency response-based ILC compensator design using circulant matrix inversion, enhancing convergence speed and transient management over traditional time domain methods.
Findings
Faster convergence compared to traditional ILC methods
Effective handling of transient errors in finite time trajectories
Numerical simulations demonstrate improved performance
Abstract
Feedback control systems do not do what you ask. The concept of bandwidth is defined to tell what components of a command are reasonably well handled. Iterative Learning Control (ILC) seeks to converge to zero error following any given finite time desired trajectory as iterations progress. The approach can be used to achieve high precision tracking in spacecraft sensors performing repeated highly accurate sensor scanning. ILC asks for zero error for a finite time tracking maneuver, containing initial transients each iteration. The purpose of this paper is to create a method of designing ILC compensators based on steady state frequency response, and have the ILC converge to zero error in spite of transients and bandwidth. In this work the inverse of the circulant matrix of Markov parameters is used as a learning gain matrix. One can show that this matrix gives the steady state frequency…
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Taxonomy
TopicsIterative Learning Control Systems · Control Systems in Engineering · Advanced Measurement and Metrology Techniques
