Iterative Learning Control for a Class of Linear Continuous-Time Switched Systems with Fixed Initial Shifts (Communications in Mathematical Research, 2019)
This paper deals with the problem of iterative learning control for aclass of linear continuous-time switched systems in the presence of a fixed initialshift. Here, the considered switched systems are operated during a finite time intervalrepetitively. According to the characteristics of the systems, a PD-type learningscheme is proposed for such switched systems with arbitrary switching rules, and thecorresponding output limiting trajectories under the action of the PD-type learningscheme are given. Based on the contraction mapping method, it is shown that thisscheme can guarantee the outputs of the systems converge uniformly to the outputlimiting trajectories of the systems over the whole time interval. Furthermore, theinitial rectifying strategies are applied to the systems for eliminating the effect of thefixed initial shift. When the learning scheme is applied to the systems, the outputsof the systems can converge to the desired reference trajectories over a pre-specifiedinterval. Finally, simulation examples illustrate the effectiveness of the proposedmethod.