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Method for controlling fuzzy neural network of active power filter based on terminal sliding mode

A technology of fuzzy neural network and power filter, applied in adaptive control, general control system, control/regulation system, etc., to overcome the precise information of the system and improve the robustness of the system

Inactive Publication Date: 2015-06-24
HOHAI UNIV CHANGZHOU
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Problems solved by technology

However, so far, although the existing patents have studied the control of active power filters from different aspects, there is no application of adaptive fuzzy neural network and non-singular terminal sliding mode control theory for current tracking of active power filters. Control and Dynamic Compensation

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  • Method for controlling fuzzy neural network of active power filter based on terminal sliding mode
  • Method for controlling fuzzy neural network of active power filter based on terminal sliding mode
  • Method for controlling fuzzy neural network of active power filter based on terminal sliding mode

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Embodiment Construction

[0067] The present invention will be further described below in conjunction with the accompanying drawings.

[0068] A fuzzy neural network control method for an active power filter based on a terminal sliding mode includes the following steps.

[0069] (1) Establishing an active power filter model

[0070] The active power filter (APF) main circuit structure of this embodiment is as follows figure 1 shown.

[0071] The basic working principle of the active power filter is to detect the harmonic current from the power system, and generate a compensation current that is equal in size to the harmonic current but opposite in polarity according to the detected harmonic current, thereby eliminating the harmonic current in the power grid. wave current.

[0072] According to circuit theory and Kirchhoff's theorem, the following three different formulas can be obtained:

[0073] v 1 ...

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Abstract

The invention discloses a method for controlling a fuzzy neural network of an active power filter based on a terminal sliding mode. The method comprises the steps that firstly, a dynamical model, containing disturbance and modeling errors, of the active power filter is established, then tracking control for a directive current is guaranteed based on nonsingular inversion terminal sliding mode control strategy, self-adaptive fuzzy neural network control strategy based on the terminal sliding mode is conducted, the defect that nonsingular inversion terminal sliding mode control strategy needs accurate information of a system is overcome, and the robustness of the system is further improved. According to the self-adaptive fuzzy neural network control strategy based on the terminal sliding mode, a fuzzy neural network structure is adopted for approaching a nonsingular inversion terminal sliding mode controller, and it is guaranteed that the parameters are bounded and a closed-loop system is stable by a self adapting rule based on a projection algorithm and Lyapunov stability theory design parameters. By means of simulation experiment, the correctness and validity of the proposed strategy are verified.

Description

technical field [0001] The patent of the present invention belongs to the active power filter technology, and in particular relates to an adaptive fuzzy neural network control method for an active power filter based on terminal sliding mode. Background technique [0002] With the popularization and application of modern power electronic technology, there are more and more various power electronic devices. The working performance and service life of equipment and electrical equipment, and even endanger the safety of the power system. Currently, external filters are mainly used for treatment. Filters are divided into two types: passive filters and active power filters. Due to the defects of passive filters that can only compensate specific harmonics, the current research on the control of electric energy problems mainly focuses on active power filters. [0003] Because it is difficult to obtain the precise mathematical model of the controlled object, the traditional control ...

Claims

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Application Information

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IPC IPC(8): G05B13/04
Inventor 侯世玺费峻涛
Owner HOHAI UNIV CHANGZHOU
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