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Self-adaptive radial basis function (RBF) neural sliding mode control method for three-phase shunt active power filter

A source filter and self-adaptive technology, applied in active power filter, harmonic reduction device, AC network to reduce harmonic/ripple, etc., can solve problems such as inability to obtain mathematical models, and achieve improved stability and robustness Rod, improve the effect of power quality

Inactive Publication Date: 2015-01-21
HOHAI UNIV CHANGZHOU
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

Due to the complexity, nonlinearity, time deformation, uncertainty and other factors in the actual system, it is impossible to obtain an accurate mathematical model, and the traditional control theory can no longer meet the requirements of industrial development, so advanced control theory has been proposed and developed

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  • Self-adaptive radial basis function (RBF) neural sliding mode control method for three-phase shunt active power filter
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  • Self-adaptive radial basis function (RBF) neural sliding mode control method for three-phase shunt active power filter

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Embodiment Construction

[0062] Below in conjunction with accompanying drawing and specific embodiment, the present invention will be further described:

[0063] See attached figure 1 , the system is an adaptive RBF neural sliding mode control system, the controlled object is a three-phase parallel active power filter, and its mathematical model can be written as x · 1 = x 2 x · 2 = f ( t ) + ag ( t ) + d ...

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Abstract

The invention discloses a self-adaptive radial basis function (RBF) neural sliding mode control method for a three-phase shunt active power filter. According to the method, a mathematical model of an Active Power Filter (APF) is established; a switching function is used as the input of an RBF neural network while a sliding mode controller is used as the output of the RBF neural network; and single-input and single-output neural sliding mode control is realized by using the learning function of the neural network. According to the control scheme, the advantages of sliding mode control, self-adaptive algorithm and the RBF neural network are synthesized, harmonic waves in supply current can be detected and tracked timely, and the purposes of eliminating harmonic waves and improving the quality of electric energy can be achieved through the production of compensation currents which are equal in size and opposite in direction. Moreover, the self-adaptive RBF sliding mode control plot can online adjust the weight of the neural network in an online manner and guarantees the stability of the system based on Lyapunov theory.

Description

Technical field: [0001] The invention relates to an adaptive RBF neural sliding mode control method for a three-phase parallel active power filter, belonging to the technical field of active power filter control. 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] The control technology of APF is one of the key technologies of APF. The control effect of APF depends to a large extent on the performance of its controller. With the development of industrial technology, the design requirements for control syst...

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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
Owner HOHAI UNIV CHANGZHOU