Robust Fractional Optimal Control Problems

Chongyang Liu (), Song Wang () and Zhaohua Gong
Additional contact information
Chongyang Liu: Shandong Technology and Business University, School of Mathematics and Information Science
Song Wang: Curtin University, School of Electrical Engineering, Computing, and Mathematical Sciences
Zhaohua Gong: Shandong Technology and Business University, School of Mathematics and Information Science

Chapter 8 in Nonlinear Fractional Optimal Control, 2026, pp 143-163 from Springer

Abstract: Abstract Parameter uncertainty is inevitably found in almost every system. In this chapter, we focus on the robust optimal control problem governed by the nonlinear fractional system with uncertain parameters, in which the system sensitivity with respect to the uncertain parameters is explicitly incorporated in the cost function. By solving the auxiliary fractional system for the system sensitivity, we proposed an equivalent optimal control problem. We then discretize the equivalent problem into the finite-dimensional optimization problem. Furthermore, we develop a gradient-based optimization algorithm for solving the finite-dimensional optimization problem. Finally, the effectiveness of the developed algorithm has been illustrated by solving two numerical examples.

Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spochp:978-981-92-0274-4_8

Ordering information: This item can be ordered from
http://www.springer.com/9789819202744

DOI: 10.1007/978-981-92-0274-4_8

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().