级联STATCOM输出的单神经元解耦控制
摘要：级联STATCOM是一个强耦合的复杂非线性系统,实现对级联STATCOM精确控制的最有效途径是对级联STATCOM进行解耦控制。本文针对普通解耦控制难以实现级联STATCOM高性能控制的问题,利用神经元出色的学习能力以及不依赖于对象模型的优点,提出了一种基于单神经元的级联STATCOM交流输出的有功和无功解耦控制策略,深入探讨了单神经元解耦控制策略的Delta学习规则、解耦机理和控制器设计方法,并在matlab/simulink仿真平台上搭建了单神经元耦控制策略的级联STATCOM系统仿真模型,给出了仿真结果。理论研究和仿真结果表明,基于单神经元解耦的STATCOM输出控制方法,与普通的解耦控制方法相比,具有响应速度快、无静差、控制精度高的优点,是一种高效的级联STATCOM解耦控制方法。
Abstract:Cascaded STATCOM is a complex nonlinear system with strong coupling relationship. The most effective way of accurate control of cascaded STATCOM is to decoupling control. Due to ordinary decoupling control method hard to achieve good control performance of cascaded STATCOM, a control strategy based on the output control of cascaded STATCOM of single neuron is proposed to decouple active and reactive power completely in this paper by taking the advantage of neuron which has good learning ability and its learning ability does not rely on model features. Delta learning rules, decoupling mechanism and designing method of decoupling control strategy for single neuron is studied deeply. A cascaded STATCOM system simulation model is established based on decoupled control strategy for single neuron in the matlab/simulink, and the simulation results are given. Theoretical and simulation results show that, by comparing with the common decoupling control method, the decoupled control method based on single neuron has such advantages as fast response, no static error, high precision control and so on, which is a highly-efficient decoupled control method for cascaded STATCOM.
标题：级联STATCOM输出的单神经元解耦控制
英文标题：Decoupling Control of Single Neuron for Cascaded STATCOM
作者：邓明锋, 粟时平, 刘桂英, 明志勇, 邓素英,
关键词：级联STATCOM, 单神经元, Delta学习规则, 解耦控制,
发表日期：2014-08-09
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