Iterative learning control for discrete-time switched singular systems

ABSTRACT

This paper deals with the problem of iterative learning control for a class of discrete-time switched singular systems with arbitrary switching rules. According to the characteristics of the systems, two types of iterative learning algorithms are proposed and the corresponding convergence conditions of the algorithms are established. Under some given assumptions, the algorithms can ensure the system state converges to the desired state trajectory on a finite time interval. Finally, two numerical examples are constructed to support the theoretical analysis.

Keywords:

• Iterative learning control
• discrete-time switched singular systems
• convergence analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 61374104 and 61773170] and the Natural Science Foundation of Guangdong Province of China [grant number 2016A030313505].