Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine
A reinforcement learning-based adaptive optimal fuzzy controller is proposed for maximum power point tracking (MPPT) control of a variable-speed permanent magnet synchronous generator-based wind energy generation system. The algorithm consists of a critic, an adaptive optimal fuzzy controller, and a...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9881498/ |
| _version_ | 1798035908341006336 |
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| author | Nga Thi-Thuy Vu Ha Duc Nguyen Anh Tuan Nguyen |
| author_facet | Nga Thi-Thuy Vu Ha Duc Nguyen Anh Tuan Nguyen |
| author_sort | Nga Thi-Thuy Vu |
| collection | DOAJ |
| description | A reinforcement learning-based adaptive optimal fuzzy controller is proposed for maximum power point tracking (MPPT) control of a variable-speed permanent magnet synchronous generator-based wind energy generation system. The algorithm consists of a critic, an adaptive optimal fuzzy controller, and an adaptive optimal fuzzy estimator. The critic is built based on an adaptive neuro-fuzzy inference system (ANFIS) network instead of the neural network as normal to reduce the computation. The error between the system output and the estimator output is used as the input of the critic. In addition, the critic is used to calculate the update law for the parameters of the adaptive optimal fuzzy controller and adaptive optimal fuzzy estimator based on minimizing the input error function. Moreover, the proposed control scheme is output feedback instead of state feedback, which does not require a system model as well as system parameters, so the system is robust to uncertainties and external disturbances. Besides, the stabilization proof is accomplished by using the Lyapunov stability theorem for the closed-loop system and the convergence of the update law. Finally, the effectiveness of the proposed reinforcement learning-based adaptive optimal fuzzy control scheme is verified through simulation with various scenarios such as step wind speed, random wind speed, and system parameter variations. Also, the comparisons with other control schemes in the state-of-art (neural network reinforcement learning based adaptive optimal fuzzy controller, PI controller) are executed to demonstrate the advantages of the proposed control scheme. |
| first_indexed | 2024-04-11T21:04:52Z |
| format | Article |
| id | doaj.art-64e9a5b9699847efbec4b5f7bfd79d6e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T21:04:52Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-64e9a5b9699847efbec4b5f7bfd79d6e2022-12-22T04:03:22ZengIEEEIEEE Access2169-35362022-01-0110957719578010.1109/ACCESS.2022.32051249881498Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind TurbineNga Thi-Thuy Vu0https://orcid.org/0000-0002-5007-1742Ha Duc Nguyen1Anh Tuan Nguyen2https://orcid.org/0000-0001-6631-3745School of Electrical and Electronics Engineering, Hanoi University of Science and Technology, Hanoi, VietnamSchool of Electrical and Electronics Engineering, Hanoi University of Science and Technology, Hanoi, VietnamFaculty of Electrical and Electronic Engineering, Phenikaa University, Ha Dong, Hanoi, VietnamA reinforcement learning-based adaptive optimal fuzzy controller is proposed for maximum power point tracking (MPPT) control of a variable-speed permanent magnet synchronous generator-based wind energy generation system. The algorithm consists of a critic, an adaptive optimal fuzzy controller, and an adaptive optimal fuzzy estimator. The critic is built based on an adaptive neuro-fuzzy inference system (ANFIS) network instead of the neural network as normal to reduce the computation. The error between the system output and the estimator output is used as the input of the critic. In addition, the critic is used to calculate the update law for the parameters of the adaptive optimal fuzzy controller and adaptive optimal fuzzy estimator based on minimizing the input error function. Moreover, the proposed control scheme is output feedback instead of state feedback, which does not require a system model as well as system parameters, so the system is robust to uncertainties and external disturbances. Besides, the stabilization proof is accomplished by using the Lyapunov stability theorem for the closed-loop system and the convergence of the update law. Finally, the effectiveness of the proposed reinforcement learning-based adaptive optimal fuzzy control scheme is verified through simulation with various scenarios such as step wind speed, random wind speed, and system parameter variations. Also, the comparisons with other control schemes in the state-of-art (neural network reinforcement learning based adaptive optimal fuzzy controller, PI controller) are executed to demonstrate the advantages of the proposed control scheme.https://ieeexplore.ieee.org/document/9881498/Adaptivefuzzy logicoptimalMPPTpermanent magnet synchronous generatorreinforcement learning |
| spellingShingle | Nga Thi-Thuy Vu Ha Duc Nguyen Anh Tuan Nguyen Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine IEEE Access Adaptive fuzzy logic optimal MPPT permanent magnet synchronous generator reinforcement learning |
| title | Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine |
| title_full | Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine |
| title_fullStr | Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine |
| title_full_unstemmed | Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine |
| title_short | Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine |
| title_sort | reinforcement learning based adaptive optimal fuzzy mppt control for variable speed wind turbine |
| topic | Adaptive fuzzy logic optimal MPPT permanent magnet synchronous generator reinforcement learning |
| url | https://ieeexplore.ieee.org/document/9881498/ |
| work_keys_str_mv | AT ngathithuyvu reinforcementlearningbasedadaptiveoptimalfuzzympptcontrolforvariablespeedwindturbine AT haducnguyen reinforcementlearningbasedadaptiveoptimalfuzzympptcontrolforvariablespeedwindturbine AT anhtuannguyen reinforcementlearningbasedadaptiveoptimalfuzzympptcontrolforvariablespeedwindturbine |