Iterative learning control for output-constrained systems with both parametric and nonparametric uncertainties

作者：Jin Xu^*; Xu Jian Xin

来源：Automatica, 2013, 49(8): 2508-2516.

DOI：10.1016/j.automatica.2013.04.039

• Iterative learning control
• Barrier composite energy function
• Parametric and nonparametric uncertainty
• Alignment condition

In this work, by proposing a Barrier Composite Energy BCEF) method with a novel Barrier Lyapunov BLF), we present a new iterative learning control (ILC) scheme for a class of single-input single-output (SISO) high order nonlinear systems to deal with output-constrained problems under alignment condition with both parametric and nonparametric system uncertainties. Nonparametric uncertainties such as norm-bounded nonlinear uncertainties satisfying local Lipschitz condition can be effectively handled. Backstepping design with the newly proposed BLF is incorporated in analysis to ensure output constraint not violated. Through rigorous analysis, we show that under this new ILC scheme, uniform convergence of state tracking error is guaranteed. In the end, an illustrative example is presented to demonstrate the efficacy of the proposed ILC scheme.

• 出版日期2013-8