Dynamic Optimization of Nonlinear Fractional Impulsive Switched Systems

Chongyang Liu (), Zhaohua Gong (), Yonghong Wu (), Benchawan Wiwatanapataphee () and Kok Lay Teo ()
Additional contact information
Chongyang Liu: Shandong Technology and Business University
Zhaohua Gong: Curtin University
Yonghong Wu: Curtin University
Benchawan Wiwatanapataphee: Curtin University
Kok Lay Teo: Sunway University

Journal of Optimization Theory and Applications, 2025, vol. 205, issue 3, No 19, 23 pages

Abstract: Abstract Optimization of fractional impulsive switched systems has various applications. In this paper, we address the dynamic optimization problem of a class of fractional impulsive switched systems, where a set of system parameters and the switching instants are decision variables to minimize a given cost functional. For this problem, we first convert these variable switching instants into the fixed instants in a new time horizon by using a proposed time-scaling transformation. This gives rise to an equivalent optimization problem with the fixed switching instants. Then, we prove that the cost functional’s gradients can be represented by the solutions of a series of auxiliary fractional impulsive systems. Furthermore, numerical schemes for solving the equivalent and auxiliary fractional impulsive system are presented. On this basis, we develop a gradient-based optimization approach to solve the dynamic optimization problem. At last, numerical results of three non-trivial examples illustrate the applicability and effectiveness of the developed optimization approach.

Keywords: Dynamic optimization; Fractional impulsive switched system; Time-scaling transformation; Numerical scheme; Numerical optimization; 49M25; 90C30; 37M15 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-025-02675-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:205:y:2025:i:3:d:10.1007_s10957-025-02675-8

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-025-02675-8

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().