@Article{CMR-34-309,
author = {Xu , GuangzhaoFu , QinDu , LiliWu , Jianrong and Yu , Pengfei},
title = {Iterative Learning Control for a Class of Linear Continuous-Time Switched Systems with Fixed Initial Shifts},
journal = {Communications in Mathematical Research },
year = {2019},
volume = {34},
number = {4},
pages = {309--328},
abstract = {<p style="text-align: justify;">This paper deals with the problem of iterative learning control for a
class of linear continuous-time switched systems in the presence of a fixed initial
shift. Here, the considered switched systems are operated during a finite time interval
repetitively. According to the characteristics of the systems, a PD-type learning
scheme is proposed for such switched systems with arbitrary switching rules, and the
corresponding output limiting trajectories under the action of the PD-type learning
scheme are given. Based on the contraction mapping method, it is shown that this
scheme can guarantee the outputs of the systems converge uniformly to the output
limiting trajectories of the systems over the whole time interval. Furthermore, the
initial rectifying strategies are applied to the systems for eliminating the effect of the
fixed initial shift. When the learning scheme is applied to the systems, the outputs
of the systems can converge to the desired reference trajectories over a pre-specified
interval. Finally, simulation examples illustrate the effectiveness of the proposed
method.</p>},
issn = {2707-8523},
doi = {https://doi.org/10.13447/j.1674-5647.2018.04.04},
url = {http://global-sci.org/intro/article_detail/cmr/13514.html}
}