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.
Original language | English |
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Pages (from-to) | 1322-1327 |
Number of pages | 6 |
Journal | IEEE Transactions on Automatic Control |
Volume | 58 |
Issue number | 5 |
DOIs | |
State | Published - May 2013 |
Keywords
- Alignment condition
- Barrier composite energy function (CEF)
- Iterative learning control (ILC)
- Parametric and nonparametric uncertainty
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering