Abstract
Time-varying Q-filtering in Iterative Learning Control (ILC) has demonstrated potential performance benefits over time-invariant Q-filtering. In this paper, LTV Q-filtering of ILC is considered for uncertain systems. Sufficient conditions for stability and the important monotonic convergence property are developed for the uncertain system. A class of LTV Q-filters that has particular benefit for rapid motion trajectories is presented, and monotonic convergence conditions are developed. The developed conditions highlight a relationship that the bandwidth can be increased locally and decreased elsewhere to localize high performance at specific times. These conditions are also iteration-length invariant and allow for significant design freedom after analysis enabling online modification of the LTV Q-filter.
| Original language | English (US) |
|---|---|
| Article number | WeA06.1 |
| Pages (from-to) | 171-177 |
| Number of pages | 7 |
| Journal | Proceedings of the American Control Conference |
| Volume | 1 |
| State | Published - 2005 |
| Event | 2005 American Control Conference, ACC - Portland, OR, United States Duration: Jun 8 2005 → Jun 10 2005 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering