Experimental Implementation of Iterative Learning Control for Processes with Stochastic Disturbances
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.
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
IEEE International Symposium on Intelligent Control
Mechanical and Aerospace Engineering
Keywords and Phrases
Deterministic Algorithms; Feedback; Iterative Methods; Learning Systems; Robots; Stochastic Systems; Three-Term Control
Article - Conference proceedings
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