Theory of well-posedness for delay differential equations via prolongations and $C^1$-prolongations: its application to state-dependent delay
Junya Nishiguchi

TL;DR
This paper develops a new theoretical framework for the well-posedness of delay differential equations using prolongations and $C^1$-prolongations, extending previous work to include state-dependent DDEs.
Contribution
It introduces notions of prolongability and Lipschitz conditions for prolongations, enabling the analysis of state-dependent DDEs which were not covered by earlier theories.
Findings
Established a theory of well-posedness using prolongations.
Extended previous results to state-dependent DDEs.
Highlighted the importance of semiflow continuity for well-posedness.
Abstract
In this paper, we establish a theory of well-posedness for delay differential equations (DDEs) via notions of \textit{prolongations} and \textit{-prolongations}, which are continuous and continuously differentiable extensions of histories to the right, respectively. In this sense, this paper serves as a continuation and an extension of the previous paper by this author (\cite{Nishiguchi 2017}). The results in \cite{Nishiguchi 2017} are applicable to various DDEs, however, the results in \cite{Nishiguchi 2017} cannot be applied to general class of state-dependent DDEs, and its extendability is missing. We find this missing link by introducing notions of (-) prolongabilities, regulation of topology by (-) prolongations, and Lipschitz conditions about (-) prolongations, etc. One of the main result claims that the continuity of the semiflow with a parameter generated by…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStability and Controllability of Differential Equations · Advanced Mathematical Modeling in Engineering · Nonlinear Dynamics and Pattern Formation
