An iterative learning control law for dynamical systems
Automatica (Journal of IFAC)
An iterative learning control theory for a class of nonlinear dynamic systems
Automatica (Journal of IFAC)
Iterative learning control in feedback systems
Automatica (Journal of IFAC)
Repositioning control of a two-link flexible arm by learning
Automatica (Journal of IFAC)
A note on convergence property of iterative learning controller with respect to sup norm
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Brief On the P-type and Newton-type ILC schemes for dynamic systems with non-affine-in-input factors
Automatica (Journal of IFAC)
Brief Nonlinear learning control for a class of nonlinear systems
Automatica (Journal of IFAC)
International Journal of Systems Science
Stability of iterative learning control with data dropouts via asynchronous dynamical system
International Journal of Automation and Computing
Hi-index | 22.15 |
In this paper, we address four major issues in the field of iterative learning control (ILC) theory and design. The first issue is concerned with ILC design in the presence of system interval uncertainties. Targeting at time-optimal (fastest convergence) and robustness properties concurrently, we formulate the ILC design into a min-max optimization problem and provide a systematic solution for linear-type ILC consisting of the first-order and higher-order ILC schemes. Inherently relating to the first issue, the second issue is concerned with the performance evaluation of various ILC schemes. Convergence speed is one of the most important factors in ILC. A learning performance index-Q-factor-is introduced, which provides a rigorous and quantified evaluation criterion for comparing the convergence speed of various ILC schemes. We further explore a key issue: how does the system dynamics affect the learning performance. By associating the time weighted norm with the supreme norm, we disclose the dynamics impact in ILC, which can be assessed by global uniform bound and monotonicity in iteration domain. Finally we address a rather controversial issue in ILC: can the higher-order ILC outperform the lower-order ILC in terms of convergence speed and robustness? By applying the min-max design, which is robust and optimal, and conducting rigorous analysis, we reach the conclusion that the Q-factor of ILC sequences of lower-order ILC is lower than that of higher-order ILC in terms of the time-weighted norm.