An Iteration-Domain Filter for Controlling Transient Growth in Iterative Learning Control
Abstract
Transient growth is a problem in Iterative Learning Control (ILC) in which the tracking error temporarily grows very large during the learning process, before converging to a small value. While some ILC algorithms can guarantee monotonic convergence, there are limitations when the model is uncertain. This paper presents a new algorithm to reduce the transient growth in ILC. An iteration domain filter, which can be applied to any linear ILC system, is proposed. The filter slows the learning process, in a controlled manner, to limit transient growth. Fundamental results relating the learning process convergence rate to explicit bounds on the transient growth are presented. Two examples that demonstrate the effectiveness of the method are presented: one in SISO design and one in network design.
Recommended Citation
Q. Liu and D. A. Bristow, "An Iteration-Domain Filter for Controlling Transient Growth in Iterative Learning Control," Proceedings of the 2010 American Control Conference, Institute of Electrical and Electronics Engineers (IEEE), Jan 2010.
Meeting Name
American Control Conference, 2010
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Adaptive Control; Control System Synthesis; Convergence of Numerical Methods; Filtering Theory; Iterative Methods; Learning Systems
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2010 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2010
