Tang, Yujie and Dall’Anese, Emiliano and Bernstein, Andrey and Low, Steven H. (2018) A Feedback-Based Regularized Primal-Dual Gradient Method for Time-Varying Nonconvex Optimization. In: 2018 IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 3244-3250. ISBN 978-1-5386-1395-5. https://resolver.caltech.edu/CaltechAUTHORS:20190204-111158128
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Abstract
This paper considers time-varying nonconvex optimization problems, utilized to model optimal operational trajectories of systems governed by possibly nonlinear physical or logical models. Algorithms for tracking a Karush-Kuhn-Tucker point are synthesized, based on a regularized primal-dual gradient method. In particular, the paper proposes a feedback-based primal-dual gradient algorithm, where analytical models for system state or constraints are replaced with actual measurements. When cost and constraint functions are twice continuously differentiable, conditions for the proposed algorithms to have bounded tracking error are derived, and a discussion of their practical implications is provided. Illustrative numerical simulations are presented for an application in power systems.
| Item Type: | Book Section | |||||||||
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| Alternate Title: | Running Primal-Dual Gradient Method for Time-Varying Nonconvex Problems | |||||||||
| Additional Information: | © 2018 IEEE. This work was supported by the Advanced Research Projects Agency-Energy (ARPA-E) under the Network Optimized Distributed Energy Systems (NODES) program. | |||||||||
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| DOI: | 10.1109/CDC.2018.8619225 | |||||||||
| Record Number: | CaltechAUTHORS:20190204-111158128 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190204-111158128 | |||||||||
| Official Citation: | Y. Tang, E. Dall'Anese, A. Bernstein and S. H. Low, "A Feedback-Based Regularized Primal-Dual Gradient Method for Time-Varying Nonconvex Optimization," 2018 IEEE Conference on Decision and Control (CDC), FL, USA, 2018, pp. 3244-3250. doi: 10.1109/CDC.2018.8619225 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 92627 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Tony Diaz | |||||||||
| Deposited On: | 04 Feb 2019 20:48 | |||||||||
| Last Modified: | 16 Nov 2021 03:52 |
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