Optimal estimation and scheduling in aquifer management using the rapid feedback control method

Ghorbanidehno, Hojat; Kokkinaki, Amalia; Kitanidis, Peter K.; Darve, Eric

doi:10.1016/j.advwatres.2017.10.011

Title: Optimal estimation and scheduling in aquifer management using the rapid feedback control method

Full Record
Other Related Research

Authors:: Ghorbanidehno, Hojat; Kokkinaki, Amalia; Kitanidis, Peter K.; Darve, Eric

Publication Date:: Fri Dec 01 00:00:00 EST 2017

Sponsoring Org.:: USDOE

OSTI Identifier:: 1549397

Grant/Contract Number:: FE0009260

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Advances in Water Resources

Additional Journal Information:: Journal Name: Advances in Water Resources Journal Volume: 110 Journal Issue: C; Journal ID: ISSN 0309-1708

Publisher:: Elsevier

Country of Publication:: United Kingdom

Language:: English

Citation Formats


                    Ghorbanidehno, Hojat, Kokkinaki, Amalia, Kitanidis, Peter K., and Darve, Eric. Optimal estimation and scheduling in aquifer management using the rapid feedback control method.  United Kingdom: N. p., 2017. 
Web.  doi:10.1016/j.advwatres.2017.10.011.

Copy to clipboard


                    Ghorbanidehno, Hojat, Kokkinaki, Amalia, Kitanidis, Peter K., & Darve, Eric. Optimal estimation and scheduling in aquifer management using the rapid feedback control method.  United Kingdom.  https://doi.org/10.1016/j.advwatres.2017.10.011

Copy to clipboard


                    Ghorbanidehno, Hojat, Kokkinaki, Amalia, Kitanidis, Peter K., and Darve, Eric. Fri .  
"Optimal estimation and scheduling in aquifer management using the rapid feedback control method".  United Kingdom.  https://doi.org/10.1016/j.advwatres.2017.10.011.

Copy to clipboard


                    
@article{osti_1549397,

  title        = {Optimal estimation and scheduling in aquifer management using the rapid feedback control method},

  author       = {Ghorbanidehno, Hojat and Kokkinaki, Amalia and Kitanidis, Peter K. and Darve, Eric},

  abstractNote = {},

  doi          = {10.1016/j.advwatres.2017.10.011},

  journal      = {Advances in Water Resources},

  number       = C,

  volume       = 110,

  place        = {United Kingdom},

  year         = {Fri Dec 01 00:00:00 EST 2017},

  month        = {Fri Dec 01 00:00:00 EST 2017}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Publisher's Version of Record
https://doi.org/10.1016/j.advwatres.2017.10.011

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 8 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Optimal estimation and scheduling in aquifer management using the rapid feedback control method

Journal Article Ghorbanidehno, Hojat ; Kokkinaki, Amalia ; Kitanidis, Peter K. ; ... - Advances in Water Resources

Not provided.
https://doi.org/10.1016/j.advwatres.2017.10.011
Home energy management based on optimal production control scheduling with unknown regime switching

Conference Dong, Jin ; Malikopoulos, Andreas ; Djouadi, Seddik M. ; ...
https://doi.org/10.23919/ACC.2017.7963255

Full Text Available
Estimation and optimal feedback control theory applied to a nuclear boiling water reactor

Journal Article Frogner, B - Trans. Am. Nucl. Soc., v. 22, p. 236
Estimation and optimal feedback control theory applied to a nuclear boiling water reactor

Journal Article Frogner, B ; Grossman, L M - Nucl. Sci. Eng., v. 58, no. 3, pp. 265-277

A linear dynamic model, a quadratic performance index, and a Gaussian stochastic noise assumption (LQG-theory) have been used to design a feedback controller for a simulated current design 1100-MW(e) boiling water reactor. The total plant power control is studied in the range of 65 to 100 percent of rated power, with main emphasis on load-following control. An extended Kalman filter used in parallel with the compensator during normal operation is suggested for on- line parameter estimation. The algorithms are considered suitable for implication in direct digital control. (auth)
Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

Journal Article Çıtmacı, Berkay ; Luo, Junwei ; Jang, Joon Baek ; ... - Chemical Engineering Research and Design

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO₂) has received increasing attention as an alternative source of carbon-based fuels. As CO₂reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO₂ process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO₂ reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On themore »« less
https://doi.org/10.1016/j.cherd.2022.06.044

Full Text Available

Similar Records