A distributed continuous-time method for non-convex QCQPs

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This paper studies non-convex Quadratically Constrained Quadratic Programmings (QCQPs) via the continuous-time optimization dynamics. We first develop an easily checkable necessary and sufficient condition that characterizes whether a KKT point will also be a saddle-point (the pair of primal and dual optima) for a non-convex QCQP. Then we analyze the semistability of the saddle-point equilibrium set with respect to the proposed optimization dynamics. We also point out that, for certain networked QCQPs, the proposed approach exhibits an intrinsic distributed computational structure.

Original languageEnglish (US)
Pages (from-to)16-23
Number of pages8
JournalSystems and Control Letters
StatePublished - Nov 2018

Bibliographical note

Funding Information:
This research was supported by the National Science Foundation, grant number CNS-1239319, USA.

Publisher Copyright:
© 2018 Elsevier B.V.


  • Distributed computational structure
  • Primal–dual optimization dynamics
  • QCQP
  • Saddle-point


Dive into the research topics of 'A distributed continuous-time method for non-convex QCQPs'. Together they form a unique fingerprint.

Cite this