HOSMD and neural network based adaptive super-twisting sliding mode control for permanent magnet synchronous generators

HOSMD and neural network based adaptive super-twisting sliding mode control for permanent magnet synchronous generators

To solve the maximum power tracking (MPT) control problem of the direct-driven wind power system, a super-twisting integral sliding mode controller with adaptive parameter estimation is designed. A high-order sliding mode differentiator is introduced as the virtual control variate filter, which solv...

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Bibliographic Details
Main Authors: Dong, X. (Author), Liu, C. (Author), Shen, J. (Author), Wang, J. (Author), Zhu, J. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
Adaptive control systems
Adaptive parameter estimation
Backstepping
Control variates
Controllers
Higher order sliding modes
High-order sliding mode differentiator
Lyapunov functions
Maximum power point trackers
Parameter estimation
Permanent magnet synchronous generator
Permanent magnet synchronous generators
Permanent magnets
Radial basis function networks
Radial basis function neural network
Radial basis function neural networks (RBF)
Sliding mode control
Sliding mode controller
Sliding-mode differentiators
Super- twisting
Super twisting algorithm
Super-twisting algorithm
Synchronous generators
Uncertainty analysis
Wind power
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