Title

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.

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.

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