Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems
<p> Due to the increased demand for reliable and resilient controls in advanced power generation systems, new control methods are required to tackle traditional problems within these systems. This work discusses a control method and an estimation method for advanced control systems. The contro...
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ndltd-PROQUEST-oai-pqdtoai.proquest.com-102636302017-07-21T04:09:04Z Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems Gu, Patrick Alternative Energy|Electrical engineering|Energy <p> Due to the increased demand for reliable and resilient controls in advanced power generation systems, new control methods are required to tackle traditional problems within these systems. This work discusses a control method and an estimation method for advanced control systems. The control method is sliding mode controls of a higher order, which is used to control the nonlinear wind energy conversion system while lessening the chattering phenomena that causes mechanical wear when using first order sliding mode controls. The super-twisting algorithm is used to create a second order sliding mode control. The estimation method is the derivation of a Resilient Extended Kalman filter, which can estimate and control the system through sensor undergoing failures with a binomial distribution rate and known mean value. Simulations on these dynamical systems are presented to show the effectiveness of the proposed control methods; the former is applied to a wind energy conversion system and the latter is applied to an single machine infinite bus. Both methods are also compared with more traditional methods in their respective applications, those being first order sliding mode controls and the Extended Kalman filter. </p><p> Southern Illinois University at Edwardsville 2017-07-20 00:00:00.0 thesis http://pqdtopen.proquest.com/#viewpdf?dispub=10263630 EN |
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language |
EN |
sources |
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topic |
Alternative Energy|Electrical engineering|Energy |
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Alternative Energy|Electrical engineering|Energy Gu, Patrick Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems |
description |
<p> Due to the increased demand for reliable and resilient controls in advanced power generation systems, new control methods are required to tackle traditional problems within these systems. This work discusses a control method and an estimation method for advanced control systems. The control method is sliding mode controls of a higher order, which is used to control the nonlinear wind energy conversion system while lessening the chattering phenomena that causes mechanical wear when using first order sliding mode controls. The super-twisting algorithm is used to create a second order sliding mode control. The estimation method is the derivation of a Resilient Extended Kalman filter, which can estimate and control the system through sensor undergoing failures with a binomial distribution rate and known mean value. Simulations on these dynamical systems are presented to show the effectiveness of the proposed control methods; the former is applied to a wind energy conversion system and the latter is applied to an single machine infinite bus. Both methods are also compared with more traditional methods in their respective applications, those being first order sliding mode controls and the Extended Kalman filter. </p><p> |
author |
Gu, Patrick |
author_facet |
Gu, Patrick |
author_sort |
Gu, Patrick |
title |
Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems |
title_short |
Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems |
title_full |
Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems |
title_fullStr |
Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems |
title_full_unstemmed |
Advanced Nonlinear Control and Estimation Methods for AC Power Generation Systems |
title_sort |
advanced nonlinear control and estimation methods for ac power generation systems |
publisher |
Southern Illinois University at Edwardsville |
publishDate |
2017 |
url |
http://pqdtopen.proquest.com/#viewpdf?dispub=10263630 |
work_keys_str_mv |
AT gupatrick advancednonlinearcontrolandestimationmethodsforacpowergenerationsystems |
_version_ |
1718502649571049472 |