Fractional-Order Iterative Learning Control with Initial State Learning for a Class of Multiagent Systems
Joint Authors
Pan, Mian
Li, Xungen
Ma, Qi
Cai, Wenyu
Lv, Shuaishuai
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-28
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
To solve the consensus problem of fractional-order multiagent systems with nonzero initial states, both open- and closed-loop PDα-type fractional-order iterative learning control are presented.
Considering the nonzero states, an initial state learning mechanism is designed.
The finite time convergences of the proposed methods are discussed in detail and strictly proved by using Lebesgue-p norm theory and fractional-order calculus.
The convergence conditions of the proposed algorithms are presented.
Finally, some simulations are applied to verify the effectiveness of the proposed methods.
American Psychological Association (APA)
Li, Xungen& Lv, Shuaishuai& Pan, Mian& Ma, Qi& Cai, Wenyu. 2020. Fractional-Order Iterative Learning Control with Initial State Learning for a Class of Multiagent Systems. Complexity،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1145409
Modern Language Association (MLA)
Li, Xungen…[et al.]. Fractional-Order Iterative Learning Control with Initial State Learning for a Class of Multiagent Systems. Complexity No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1145409
American Medical Association (AMA)
Li, Xungen& Lv, Shuaishuai& Pan, Mian& Ma, Qi& Cai, Wenyu. Fractional-Order Iterative Learning Control with Initial State Learning for a Class of Multiagent Systems. Complexity. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1145409
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1145409