Iterative learning control for the linear model with a singular feedthrough term via LQAT

Chia Hsing Chen, Jason Sheng-Hon Tsai, Shu-Mei Guo, Leang San Shieh

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose an iterative learning control (ILC) strategy for the continuous-time linear time-invariant (LTI) model with a singular feedthrough term, from input to output. By combining with the linear quadratic analogue tracker (LQAT), the transient performance improvement is achieved through the initial control input, at the 0th iteration, obtained by the LQAT. Initially, we propose the PD-type iterative learning controller together with initial statelearning law, and sufficient condition to guarantee the convergence of tracking error is derived. Thereafter, a novel LQAT, with a high-gain property, for the model under consideration is constructed. The role of LQAT is to obtain first (initial) control input of the ILC scheme. A numerical example illustrates the effectiveness of the proposed strategy.

Original languageEnglish
Pages (from-to)4283-4294
Number of pages12
JournalApplied Mathematical Sciences
Volume6
Issue number85-88
Publication statusPublished - 2012 Jul 24

All Science Journal Classification (ASJC) codes

  • Applied Mathematics

Fingerprint Dive into the research topics of 'Iterative learning control for the linear model with a singular feedthrough term via LQAT'. Together they form a unique fingerprint.

Cite this