Extremum seeking control with data-based disturbance feedforward

Sava Marinkov; Bram de Jager; Maarten Steinbuch

doi:10.1109/ACC.2014.6858832

Extremum seeking control with data-based disturbance feedforward

Sava Marinkov, Bram de Jager, Maarten Steinbuch

Mechanical Engineering

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

10 Citations (Scopus)

5 Downloads (Pure)

Abstract

This paper presents a practical extension to the classical gradient-based extremum seeking control for the case when the disturbances responsible for the changes in the extremum of a related performance function can be measured. The additional information is used to improve accuracy, convergence speed and robustness of the underlying ESC scheme. Based on the disturbance measurements a map between them and the optimal inputs is iteratively constructed and used as an extremum seeking feedforward. A supervising state-machine is designed to regulate feedforward and search processes ensuring the latter is conducted in the close vicinity of an extremum. The search is based on the sinusoidal input perturbation introduced each time the disturbance is detected and removed once the optimal set-point is identified. Simulation results for the cases of photovoltaic and turbine driven electrical generator systems demonstrate the benefits of the presented design.

Original language	English
Title of host publication	Proceedings of the American Control Conference, 4-6 June 2014, Portland, Oregon
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	3627-3632
Number of pages	6
ISBN (Print)	9781479932726
DOIs	https://doi.org/10.1109/ACC.2014.6858832
Publication status	Published - 2014
Event	2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA - Hilton Portland & Executive Tower , Portland, OR, United States Duration: 4 Jun 2014 → 6 Jun 2014 http://acc2014.a2c2.org/

Conference

Conference	2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA
Abbreviated title	ACC 2014
Country/Territory	United States
City	Portland, OR
Period	4/06/14 → 6/06/14
Internet address	http://acc2014.a2c2.org/

Keywords

Control applications
Estimation
Optimization algorithms

UN SDGs

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

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10.1109/ACC.2014.6858832

Cite this

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abstract = "This paper presents a practical extension to the classical gradient-based extremum seeking control for the case when the disturbances responsible for the changes in the extremum of a related performance function can be measured. The additional information is used to improve accuracy, convergence speed and robustness of the underlying ESC scheme. Based on the disturbance measurements a map between them and the optimal inputs is iteratively constructed and used as an extremum seeking feedforward. A supervising state-machine is designed to regulate feedforward and search processes ensuring the latter is conducted in the close vicinity of an extremum. The search is based on the sinusoidal input perturbation introduced each time the disturbance is detected and removed once the optimal set-point is identified. Simulation results for the cases of photovoltaic and turbine driven electrical generator systems demonstrate the benefits of the presented design.",

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Marinkov, S, de Jager, B & Steinbuch, M 2014, Extremum seeking control with data-based disturbance feedforward. in Proceedings of the American Control Conference, 4-6 June 2014, Portland, Oregon. Institute of Electrical and Electronics Engineers, Piscataway, pp. 3627-3632, 2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA, Portland, OR, United States, 4/06/14. https://doi.org/10.1109/ACC.2014.6858832

Extremum seeking control with data-based disturbance feedforward. / Marinkov, Sava; de Jager, Bram; Steinbuch, Maarten.
Proceedings of the American Control Conference, 4-6 June 2014, Portland, Oregon. Piscataway: Institute of Electrical and Electronics Engineers, 2014. p. 3627-3632.

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

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AB - This paper presents a practical extension to the classical gradient-based extremum seeking control for the case when the disturbances responsible for the changes in the extremum of a related performance function can be measured. The additional information is used to improve accuracy, convergence speed and robustness of the underlying ESC scheme. Based on the disturbance measurements a map between them and the optimal inputs is iteratively constructed and used as an extremum seeking feedforward. A supervising state-machine is designed to regulate feedforward and search processes ensuring the latter is conducted in the close vicinity of an extremum. The search is based on the sinusoidal input perturbation introduced each time the disturbance is detected and removed once the optimal set-point is identified. Simulation results for the cases of photovoltaic and turbine driven electrical generator systems demonstrate the benefits of the presented design.

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KW - Estimation

KW - Optimization algorithms

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Extremum seeking control with data-based disturbance feedforward

Abstract

Conference

Keywords

UN SDGs

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