1. PDα-type iterative learning control with initial state learning for fractional-order systems
- Author
-
Kejun Zhang and Fen Liu
- Subjects
0209 industrial biotechnology ,lebesgue-p norm ,Iterative learning control ,initial state learning ,General Engineering ,iterative learning control ,TL1-4050 ,02 engineering and technology ,State (functional analysis) ,Type (model theory) ,01 natural sciences ,fractional-order ,010101 applied mathematics ,020901 industrial engineering & automation ,Order (group theory) ,Applied mathematics ,0101 mathematics ,Mathematics ,Motor vehicles. Aeronautics. Astronautics - Abstract
In order to eliminate the influence of the arbitrary initial state on the systems, open-loop and open-close-loop PDα-type fractional-order iterative learning control (FOILC) algorithms with initial state learning are proposed for a class of fractional-order linear continuous-time systems with an arbitrary initial state. In the sense of Lebesgue-p norm, the sufficient conditions for the convergence of PDα-type algorithms are disturbed in the iteration domain by taking advantage of the generalized Young inequality of convolution integral. The results demonstrate that under these novel algorithms, the convergences of the tracking error are can be guaranteed. Numerical simulations support the effectiveness and correctness of the proposed algorithms.
- Published
- 2021