Experimental Implementation of Iterative Learning Control for Processes with Stochastic Disturbances
Abstract
A number of iterative learning control algorithms have been developed in a stochastic setting in recent years. The results currently available are in the form of fundamental systems theoretical properties and associated algorithm development. This paper reports results from the application of a stochastic algorithm on a gantry robot system that has been used in the benchmarking a range of deterministic algorithms. These results confirm that this algorithm is capable of delivering good performance in the experimental domain, including comparison against an alternative.
Recommended Citation
Z. Cai et al., "Experimental Implementation of Iterative Learning Control for Processes with Stochastic Disturbances," IEEE International Symposium on Intelligent Control, Institute of Electrical and Electronics Engineers (IEEE), Jan 2011.
The definitive version is available at https://doi.org/10.1109/ISIC.2011.6045408
Meeting Name
IEEE International Symposium on Intelligent Control
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Deterministic Algorithms; Feedback; Iterative Methods; Learning Systems; Robots; Stochastic Systems; Three-Term Control
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2011 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2011
