Abstract
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 language | English (US) |
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Pages (from-to) | 16-23 |
Number of pages | 8 |
Journal | Systems and Control Letters |
Volume | 121 |
DOIs | |
State | Published - 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.
Keywords
- Distributed computational structure
- Primal–dual optimization dynamics
- QCQP
- Saddle-point