Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-37105-9_15
Title: Analysis on data-based integrated learning control for batch processes
Authors: Jia, L.
Cao, L.
Chiu, M. 
Keywords: Batch processes
Integrated learning control system
Single neuron predictive controller (SNPC)
Issue Date: Sep-2013
Source: Jia, L.,Cao, L.,Chiu, M. (2013-09). Analysis on data-based integrated learning control for batch processes. Communications in Computer and Information Science 355 : 130-138. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-37105-9_15
Abstract: A novel integrated learning control system is presented in this paper. It systematically integrates discrete-time (batch-axis) information and continuous- time (time-axis) information into one uniform frame. More specifically, the iterative learning controller is designed in the domain of batch-axis, while an adaptive single neuron predictive controller (SNPC) in the domain of timeaxis. In addition, the convergence and tracking performance of the proposed integrated learning control system are firstly given rigorous description and proof. Lastly, to verify the effectiveness of the proposed integrated control system, it is applied to a benchmark batch process, in comparison with ILC recently developed. © Springer-Verlag Berlin Heidelberg 2013.
Source Title: Communications in Computer and Information Science
URI: http://scholarbank.nus.edu.sg/handle/10635/63482
ISSN: 18650929
DOI: 10.1007/978-3-642-37105-9_15
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