Robustness Convergence for Iterative Learning Tracking Control Applied to Repetitfs Systems

Convergence of iterative methods applied to Burgers-Huxley equation

Iterative Learning Control for uncertain systems: Robust monotonic convergence analysis

In this paper, we present a novel Robust Monotonic Convergence (RMC) analysis approach for finite time interval Iterative Learning Control (ILC) for uncertain systems. For that purpose, a finite time interval model for uncertain systems is introduced. This model is subsequently used in an RMC analysis based on μ analysis. As a result, we can handle additive andmultiplicative uncertainty models ...

convergence of iterative methods applied to burgers-huxley equation

Iterative learning identification and control for dynamic systems described by NARMAX model

A new iterative learning controller is proposed for a general unknown discrete time-varying nonlinear non-affine system represented by NARMAX (Nonlinear Autoregressive Moving Average with eXogenous inputs) model. The proposed controller is composed of an iterative learning neural identifier and an iterative learning controller. Iterative learning control and iterative learning identification ar...

On the convergence of iterative learning control

We derive frequency-domain criteria for the convergence of linear iterative learning control (ILC) on finite-time intervals that are less restrictive than existing ones in the literature. In particular, the former can be used to establish the convergence of ILC in certain cases where the latter are violated. The results cover ILC with non-causal filters and provide insights into the transient b...