Enhancing trajectory tracking for a class of process control problems using iterative learning

Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0952-1976(02)00008-8

Title:	Enhancing trajectory tracking for a class of process control problems using iterative learning
Authors:	Xu, J.-X. Lee, T.-H. Tan, Y.
Keywords:	Enhance tracking Filter-based iterative learning control Frequency convergence analysis
Issue Date:	Feb-2002
Citation:	Xu, J.-X., Lee, T.-H., Tan, Y. (2002-02). Enhancing trajectory tracking for a class of process control problems using iterative learning. Engineering Applications of Artificial Intelligence 15 (1) : 53-64. ScholarBank@NUS Repository. https://doi.org/10.1016/S0952-1976(02)00008-8
Abstract:	A method of enhancing tracking in repetitive processes, which can be approximated by a first-order plus dead-time model is presented. Enhancement is achieved through filter-based iterative learning control (ILC). The design of the ILC parameters is conducted in frequency domain, which guarantees the convergence property in iteration domain. The filter-based ILC can be easily added to existing control systems. To clearly demonstrate the features of the proposed ILC, a water heating process under a PI controller is used as a testbed. The empirical results show improved tracking performance with iterative learning. © 2002 Elsevier Science Ltd. All rights reserved.
Source Title:	Engineering Applications of Artificial Intelligence
URI:	http://scholarbank.nus.edu.sg/handle/10635/55898
ISSN:	09521976
DOI:	10.1016/S0952-1976(02)00008-8
Appears in Collections:	Staff Publications

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