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首页> 外文期刊>Central European Journal of Engineering >An adaptive neuro fuzzy inference system controlled space cector pulse width modulation based HVDC: light transmission system under AC fault conditions
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An adaptive neuro fuzzy inference system controlled space cector pulse width modulation based HVDC: light transmission system under AC fault conditions

机译：基于HVDC的自适应神经模糊推理系统控制的空间矢量脉宽调制：交流故障条件下的输电系统。

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摘要

In HVDC Light transmission systems, converter control is one of the major fields of present day research works. In this paper, fuzzy logic controller is utilized for controlling both the converters of the space vector pulse width modulation (SVPWM) based HVDC Light transmission systems. Due to its complexity in the rule base formation, an intelligent controller known as adaptive neuro fuzzy inference system (ANFIS) controller is also introduced in this paper. The proposed ANFIS controller changes the PI gains automatically for different operating conditions. A hybrid learning method which combines and exploits the best features of both the back propagation algorithm and least square estimation method is used to train the 5-layer ANFIS controller. The performance of the proposed ANFIS controller is compared and validated with the fuzzy logic controller and also with the fixed gain conventional PI controller. The simulations are carried out in the MATLAB/SIMULINK environment. The results reveal that the proposed ANFIS controller is reducing power fluctuations at both the converters. It also improves the dynamic performance of the test power system effectively when tested for various ac fault conditions.
机译：在高压直流输电系统中，转换器控制是当今研究工作的主要领域之一。在本文中，模糊逻辑控制器用于控制基于空间矢量脉冲宽度调制（SVPWM）的HVDC输电系统的两个转换器。由于其在规则库形成中的复杂性，本文还介绍了一种称为自适应神经模糊推理系统（ANFIS）的智能控制器。建议的ANFIS控制器会针对不同的工作条件自动更改PI增益。结合并利用反向传播算法和最小二乘估计方法的最佳功能的混合学习方法来训练5层ANFIS控制器。所提出的ANFIS控制器的性能与模糊逻辑控制器以及固定增益的常规PI控制器进行了比较和验证。仿真是在MATLAB / SIMULINK环境中进行的。结果表明，所提出的ANFIS控制器正在减小两个转换器的功率波动。在各种交流故障条件下进行测试时，它还可以有效地提高测试电源系统的动态性能。

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