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Hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage

A neural network inverse and hybrid magnetic bearing technology, which is applied in the control of electromechanical brakes, control systems, control generators, etc., to achieve excellent dynamic and static characteristics, improved approximation accuracy and convergence speed, and good learning ability

Pending Publication Date: 2022-07-22
JIANGSU UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problems existing in the existing hybrid magnetic bearing control technology for flywheel energy storage, and propose a hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage with strong robustness and fast learning speed

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  • Hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage
  • Hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage
  • Hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage

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Embodiment Construction

[0019] like figure 1 As shown, the hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage of the present invention is composed of two dynamic prediction modules 61, 61 and an LM neural network inverse system 5, and the output terminals of the two dynamic prediction modules 61, 61 are composed of Both are connected in series with the input end of the LM neural network inverse system 5, and the output end of the LM neural network inverse system 5 is connected with the compound controlled object 1 including the six-pole radial-axial hybrid magnetic bearing 2 for flywheel energy storage.

[0020] The output of the composite plant 1 is the radial displacement x, y and the axial displacement z of the six-pole radial-axial hybrid magnetic bearing for flywheel energy storage. The input of the first dynamic prediction module 61 is a random weight ω and a threshold θ and a reference weight ω * and the reference threshold θ * , the output is...

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Abstract

The invention discloses a hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage, the output ends of two dynamic prediction modules are connected in series with the input end of an LM neural network inverse system, the first dynamic prediction module is composed of two series branches, and the second dynamic prediction module is composed of three series branches and a composite signal calculation module. Each series branch is formed by sequentially connecting a feedback correction module, a control increment calculation module, a predicted value calculation module and an optimal value calculation module in series; the input of the first series branch is a weight value and a reference weight value, the output of the first series branch is an optimal initial weight value, the input of the second series branch is a threshold value and a reference threshold value, the output of the second series branch is an optimal initial threshold value, the advantages of dynamic prediction, LM neural network control and an inverse system are combined, the initial weight value and the threshold value of the LM neural network are optimized by adopting a dynamic prediction module, and the optimal initial weight value is obtained. And independent accurate control among three degrees of freedom of the hybrid magnetic bearing for flywheel energy storage is realized.

Description

technical field [0001] The invention belongs to the technical field of electric transmission control equipment, and relates to a decoupling control technology of a hybrid magnetic bearing for flywheel energy storage, in particular to a hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage, which is suitable for multi-variable, nonlinear, Decoupling Control of Hybrid Magnetic Bearings for Strongly Coupled Flywheel Energy Storage. Background technique [0002] At present, the main energy storage methods are chemical energy storage, superconducting energy storage and physical energy storage. Among them, flywheel energy storage is a physical energy storage method. It has become the focus of new energy due to its high energy storage density, long service life, and high energy conversion efficiency. It has been successfully used in uninterruptible power supplies, wind power stations and other fields. The traditional flywheel energy st...

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Application Information

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IPC IPC(8): H02P21/00H02P21/14H02K7/02
CPCH02P21/0014H02P21/14H02K7/025
Inventor 郦依领马志豪朱剑毫赵腾飞郭龙雨朱熀秋
Owner JIANGSU UNIV
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