TY - GEN
T1 - Deterministic Tracking for Continuous-Time ILC Systems with Nonrepetitive Time Intervals
AU - Zhang, Jingyao
AU - Meng, Deyuan
N1 - Publisher Copyright:
© 2021 American Automatic Control Council.
PY - 2021/5/25
Y1 - 2021/5/25
N2 - This paper is aimed at realizing robust tracking tasks for continuous-time iterative learning control (ILC) systems subject to nonrepetitive time intervals. A modified P-type ILC algorithm is proposed such that the deterministic tracking of continuous-time ILC can be ensured in the presence of the nonrepetitive time intervals. Moreover, a convergence analysis approach to continuous-time ILC is given by applying an extended contraction mapping-based method. An example is also included to verify our derived robust ILC results.
AB - This paper is aimed at realizing robust tracking tasks for continuous-time iterative learning control (ILC) systems subject to nonrepetitive time intervals. A modified P-type ILC algorithm is proposed such that the deterministic tracking of continuous-time ILC can be ensured in the presence of the nonrepetitive time intervals. Moreover, a convergence analysis approach to continuous-time ILC is given by applying an extended contraction mapping-based method. An example is also included to verify our derived robust ILC results.
UR - https://www.scopus.com/pages/publications/85111911709
U2 - 10.23919/ACC50511.2021.9482901
DO - 10.23919/ACC50511.2021.9482901
M3 - 会议稿件
AN - SCOPUS:85111911709
T3 - Proceedings of the American Control Conference
SP - 2218
EP - 2223
BT - 2021 American Control Conference, ACC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 American Control Conference, ACC 2021
Y2 - 25 May 2021 through 28 May 2021
ER -