Multivariable optimal point tracking algorithm

Carlos Andrés Devia; Diego Patino

doi:10.1109/CCA.2016.7587985

Multivariable optimal point tracking algorithm

Carlos Andrés Devia, Diego Patino

Department of Electronic Engineering

Universidad Javeriana

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper presents a method to track local optimal points in unknown multivariable non-convex time-varying cost functions. The main contribution of this method is that is model-free, the tracking property is proven and an error bound is given. Next several simulations are performed. An example of Maximum Power Point Tracking in Photovoltaic Panels is presented including the successful tracking of the Maximum Power Point. Finally conclusions and further work are discussed.

Original language	English
Title of host publication	2016 IEEE Conference on Control Applications, CCA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1294-1299
Number of pages	6
ISBN (Electronic)	9781509007554
DOIs	https://doi.org/10.1109/CCA.2016.7587985
State	Published - 10 Oct 2016
Event	2016 IEEE Conference on Control Applications, CCA 2016 - Buenos Aires, Argentina Duration: 19 Sep 2016 → 22 Sep 2016

Publication series

Name	2016 IEEE Conference on Control Applications, CCA 2016

Conference

Conference	2016 IEEE Conference on Control Applications, CCA 2016
Country/Territory	Argentina
City	Buenos Aires
Period	19/09/16 → 22/09/16

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/CCA.2016.7587985

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title = "Multivariable optimal point tracking algorithm",

abstract = "This paper presents a method to track local optimal points in unknown multivariable non-convex time-varying cost functions. The main contribution of this method is that is model-free, the tracking property is proven and an error bound is given. Next several simulations are performed. An example of Maximum Power Point Tracking in Photovoltaic Panels is presented including the successful tracking of the Maximum Power Point. Finally conclusions and further work are discussed.",

author = "Devia, {Carlos Andr{\'e}s} and Diego Patino",

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year = "2016",

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doi = "10.1109/CCA.2016.7587985",

language = "English",

series = "2016 IEEE Conference on Control Applications, CCA 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Devia, CA & Patino, D 2016, Multivariable optimal point tracking algorithm. in 2016 IEEE Conference on Control Applications, CCA 2016., 7587985, 2016 IEEE Conference on Control Applications, CCA 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1294-1299, 2016 IEEE Conference on Control Applications, CCA 2016, Buenos Aires, Argentina, 19/09/16. https://doi.org/10.1109/CCA.2016.7587985

Multivariable optimal point tracking algorithm. / Devia, Carlos Andrés; Patino, Diego.
2016 IEEE Conference on Control Applications, CCA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1294-1299 7587985 (2016 IEEE Conference on Control Applications, CCA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Patino, Diego

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N2 - This paper presents a method to track local optimal points in unknown multivariable non-convex time-varying cost functions. The main contribution of this method is that is model-free, the tracking property is proven and an error bound is given. Next several simulations are performed. An example of Maximum Power Point Tracking in Photovoltaic Panels is presented including the successful tracking of the Maximum Power Point. Finally conclusions and further work are discussed.

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PB - Institute of Electrical and Electronics Engineers Inc.

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Multivariable optimal point tracking algorithm

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