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Adaptive RBF (radial basis function) neural network control technique for three-phase parallel active filters

A technology of neural network control and source filter, applied in active power filter, AC network to reduce harmonic/ripple, harmonic reduction device, etc., can solve problems such as increased loss, poor power quality, and excessive current , to achieve the effect of canceling the harmonic

Inactive Publication Date: 2015-04-01
HOHAI UNIV CHANGZHOU
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Problems solved by technology

[0002] With the application of a large number of nonlinear loads, the harmonic content in the power grid is increasing, resulting in poorer power quality
Harmonics will cause a series of hazards such as overheating of equipment, increased loss, and excessive current, which must be suppressed

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  • Adaptive RBF (radial basis function) neural network control technique for three-phase parallel active filters
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  • Adaptive RBF (radial basis function) neural network control technique for three-phase parallel active filters

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Embodiment Construction

[0068] In order to further explain the technical means and effects of the present invention to achieve the intended purpose of the invention, the specific implementation, structure, features and effects of the present invention will be described in detail below in conjunction with the accompanying drawings and preferred embodiments. rear.

[0069] Such as figure 1 As shown, a three-phase parallel active filter adaptive RBF neural network control method comprises the following steps:

[0070] A, design adaptive RBF neural network controller for three-phase parallel active filter; Described adaptive RBF neural network controller is designed based on RBF neural network and adaptive algorithm;

[0071] b. Establish the numerical sequence model of the controlled object three-phase parallel active filter , where x is the compensation current, f(x) is the unknown equation, b is the unknown constant, u is the switching function, which is the output of the RBF neural network control...

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Abstract

The invention relates to an adaptive RBF (radial basis function) neural network control technique for three-phase parallel active filters, belonging to an active power filter control technique. The invention provides an adaptive RBF neural network control method for three-phase parallel active power filters, which is used for controlling a compensation current output by a three-phase parallel active power filter through a controller, thereby eliminating harmonic waves and improving the power supply quality of a power grid. According to an adaptive control rule provided by the invention, the boundedness of weights is ensured, and the stability of the controller is proved by using a Lyapunov stability theory; and simulation results show that the control method effectively reduces the distortion factor of harmonic waves and is good in dynamic response, and when parameters change, the controller has good robustness and adaptability.

Description

technical field [0001] The invention relates to a three-phase parallel active filter adaptive RBF neural network control method, which belongs to the active power filter control technology. Background technique [0002] With the application of a large number of nonlinear loads, the harmonic content in the power grid is increasing day by day, resulting in worse and worse power quality. Harmonics can cause a series of hazards such as overheating of equipment, increased loss, and excessive current, which must be suppressed. Compared with the passive power filter, the active power filter (APF) can more effectively deal with the harmonics and power factor of the changing load. "The most effective means. [0003] APF research at home and abroad has made great progress, and has been widely used. With the rapid development of the precision, speed and reliability of hardware equipment, the requirements for high-performance algorithms and real-time control are getting higher and hi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/01
CPCY02E40/40Y02E40/22Y02E40/20
Inventor 王哲费峻涛戴卫力华民刚王琮
Owner HOHAI UNIV CHANGZHOU
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