Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2012.2223353
Title: State-constrained iterative learning control for a class of MIMO systems
Authors: Xu, J.-X. 
Jin, X.
Keywords: Alignment condition
Barrier composite energy function (CEF)
Iterative learning control (ILC)
Parametric and nonparametric uncertainty
Issue Date: May-2013
Citation: Xu, J.-X., Jin, X. (2013-05). State-constrained iterative learning control for a class of MIMO systems. IEEE Transactions on Automatic Control 58 (5) : 1322-1327. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2012.2223353
Abstract: In this note, we present a novel iterative learning control (ILC) method for a class of state-constrained multi-input multi-output (MIMO) nonlinear system under state alignment condition with both parametric and nonparametric uncertainties. Nonparametric uncertainties such as norm-bounded nonlinear uncertainties satisfying local Lipschitz condition can be effectively handled. Barrier Composite Energy Function (BCEF) scheme with a novel Barrier Lyapunov Function is proposed to facilitate the analysis of state tracking error convergence while satisfying the state constraints. In the end, an illustrative example is shown to demonstrate the efficacy of the proposed ILC method. © 2012 IEEE.
Source Title: IEEE Transactions on Automatic Control
URI: http://scholarbank.nus.edu.sg/handle/10635/83066
ISSN: 00189286
DOI: 10.1109/TAC.2012.2223353
Appears in Collections:Staff Publications

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