Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID
When wind speeds are above the rated speed of variable speed variable pitch wind turbines, pitch angles are changed to keep output powers and rotor speeds at their rated values. For wind turbines with nonlinear and complex structure, conventional PID variable pitch controller is difficult to achieve...
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doaj-9c3a513e32c74f8aac2915a235db4cfd2021-03-30T02:58:55ZengIEEEIEEE Access2169-35362020-01-018717827179710.1109/ACCESS.2020.29879129066988Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PIDHaijun Ren0https://orcid.org/0000-0002-8211-3820Bin Hou1Gao Zhou2Li Shen3Chong Wei4Qi Li5School of Advanced Manufacture Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Advanced Manufacture Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Advanced Manufacture Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Advanced Manufacture Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Advanced Manufacture Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Advanced Manufacture Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaWhen wind speeds are above the rated speed of variable speed variable pitch wind turbines, pitch angles are changed to keep output powers and rotor speeds at their rated values. For wind turbines with nonlinear and complex structure, conventional PID variable pitch controller is difficult to achieve precise control. In this paper, a variable pitch controller combining back-propagation(BP) neural network with PID (BP-PID) is proposed. By real-time detecting the deviation of the rotor speeds, the BP neural network with self-learning and weighting coefficient correction capability is used to adjust the PID parameters online and further to achieve the optimal combination of the PID parameters. Considering various uncertain disturbances and parameter changes on the mechanical components of the wind turbines, an active disturbance rejection pitch controller of the wind turbines is designed based on BP-PID algorithm. Combined with a tracking differentiator, an extended state observer (ESO) is employed to observe the state and disturbance of the system. In addition, in order to compensate the BP-PID variable pitch controller, nonlinear state error feedback control laws are designed by configuring nonlinear structures according to the state deviation between the extended state observer and the tracking differentiator. The simulation results show that the variable pitch active disturbance rejection control (ADRC) based on BP-PID can effectively estimate the system states and disturbances. And the proposed controller has good dynamic performance and strong robustness.https://ieeexplore.ieee.org/document/9066988/Wind turbinepitch controlBP-PIDactive disturbance rejection controlextended state observer |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Haijun Ren Bin Hou Gao Zhou Li Shen Chong Wei Qi Li |
spellingShingle |
Haijun Ren Bin Hou Gao Zhou Li Shen Chong Wei Qi Li Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID IEEE Access Wind turbine pitch control BP-PID active disturbance rejection control extended state observer |
author_facet |
Haijun Ren Bin Hou Gao Zhou Li Shen Chong Wei Qi Li |
author_sort |
Haijun Ren |
title |
Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID |
title_short |
Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID |
title_full |
Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID |
title_fullStr |
Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID |
title_full_unstemmed |
Variable Pitch Active Disturbance Rejection Control of Wind Turbines Based on BP Neural Network PID |
title_sort |
variable pitch active disturbance rejection control of wind turbines based on bp neural network pid |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
When wind speeds are above the rated speed of variable speed variable pitch wind turbines, pitch angles are changed to keep output powers and rotor speeds at their rated values. For wind turbines with nonlinear and complex structure, conventional PID variable pitch controller is difficult to achieve precise control. In this paper, a variable pitch controller combining back-propagation(BP) neural network with PID (BP-PID) is proposed. By real-time detecting the deviation of the rotor speeds, the BP neural network with self-learning and weighting coefficient correction capability is used to adjust the PID parameters online and further to achieve the optimal combination of the PID parameters. Considering various uncertain disturbances and parameter changes on the mechanical components of the wind turbines, an active disturbance rejection pitch controller of the wind turbines is designed based on BP-PID algorithm. Combined with a tracking differentiator, an extended state observer (ESO) is employed to observe the state and disturbance of the system. In addition, in order to compensate the BP-PID variable pitch controller, nonlinear state error feedback control laws are designed by configuring nonlinear structures according to the state deviation between the extended state observer and the tracking differentiator. The simulation results show that the variable pitch active disturbance rejection control (ADRC) based on BP-PID can effectively estimate the system states and disturbances. And the proposed controller has good dynamic performance and strong robustness. |
topic |
Wind turbine pitch control BP-PID active disturbance rejection control extended state observer |
url |
https://ieeexplore.ieee.org/document/9066988/ |
work_keys_str_mv |
AT haijunren variablepitchactivedisturbancerejectioncontrolofwindturbinesbasedonbpneuralnetworkpid AT binhou variablepitchactivedisturbancerejectioncontrolofwindturbinesbasedonbpneuralnetworkpid AT gaozhou variablepitchactivedisturbancerejectioncontrolofwindturbinesbasedonbpneuralnetworkpid AT lishen variablepitchactivedisturbancerejectioncontrolofwindturbinesbasedonbpneuralnetworkpid AT chongwei variablepitchactivedisturbancerejectioncontrolofwindturbinesbasedonbpneuralnetworkpid AT qili variablepitchactivedisturbancerejectioncontrolofwindturbinesbasedonbpneuralnetworkpid |
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1724184221079044096 |