Metacognitive fuzzy neural network-based active power filter sliding mode control method

A technology of fuzzy neural network and power filter, applied in adaptive control, general control system, control/regulation system, etc., can solve the problems of system instability, low robustness, inconvenience, etc.

Active Publication Date: 2018-11-16
HOHAI UNIV CHANGZHOU
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Problems solved by technology

However, the robustness of adaptive control to external disturbances is very low, and it is easy to make the system unstable.
[0004] This shows that above-mentioned existing active power filter obviously still has inconvenience and defect in use, a

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  • Metacognitive fuzzy neural network-based active power filter sliding mode control method
  • Metacognitive fuzzy neural network-based active power filter sliding mode control method
  • Metacognitive fuzzy neural network-based active power filter sliding mode control method

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Embodiment Construction

[0080] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0081] In power grid applications, the application of three-phase alternating current accounts for the majority, so the present invention mainly studies the situation of being used in a three-phase three-wire system. like figure 1 is the basic circuit topology diagram of the existing three-phase three-wire parallel voltage-type active power filter, v s1 ,v s2 ,v s3 is the grid voltage, i s1 ,i s2 ,i s3 is the supply current, i L1 ,i L2 ,i L3 is the load current, v 1 ,v 2 ,v 3 is the voltage at the common connection point, i 1 ,i 2 ,i 3 is the filter output compensation current, C is the DC side capacitance, v dc is the DC side capacitor voltage, i dc is the DC side capacitor cur...

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Abstract

The invention discloses a metacognitive fuzzy neural network-based active power filter sliding mode control method. The method includes the following steps that: S1, an active power filter dynamic equation is established; and S2, a control law is designed to be an equation described in the descriptions of the invention, and f<^> is an estimation value obtained by using a metacognitive fuzzy neuralnetwork f(x). According to the method of the present invention, the metacognitive method is adopted to adjust the structure of the fuzzy neural network online; the structure of the fuzzy neural network is dynamically adjusted according to a tracking error design rule addition, parameter update and rule deletion algorithm; and therefore, the compensation current tracking performance and system robustness of an active power filter system under parameter perturbation and external interference can be improved.

Description

technical field [0001] The invention relates to the technical field of active power filter control, in particular to a sliding mode control method for an active power filter based on a metacognitive fuzzy neural network. 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 passive filters and active filters. Since the passive filter can only compensate specific harmonics and other defects, the current research on the control of electric energy problems mainly focuses on the active filter. The active filter can track and compensate the harmonics with changing frequency and amplitude. It can not only compensate each harmonic, but also suppress flicker a...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 袁杉杉侯世玺费峻涛储云迪
Owner HOHAI UNIV CHANGZHOU
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