基于GSA优化模糊神经网络的静止无功补偿器的电压控制研究  

The Voltage Control of Static Reactive Power Compensator Based on GSA Optimizing Fuzzy Neural Network

作　　者：谭广通[1] Tan Guangtong(91245 Troops, Huludao, 125000)

机构地区：[1]91245部队,葫芦岛125000

出　　处：《微型电脑应用》2018年第4期30-32,49,共4页Microcomputer Applications

摘　　要：针对模糊PID和PID控制无法满足静止无功补偿器(static var Compensator,SVC)的电压控制精度要求,提出了一种基于引力搜索算法(gravitational search algorithm,GSA)优化模糊PID的SVC的电压控制算法。在SVC的输入量和输出量模糊化处理的基础上,运用GSA算法优化模糊规则、比例系数和量化因子。实验结果表明,GSA-PID能实现SVC的最优化控制。Because the control accuracy of PID and fuzzy PID cannot meet control requirement for the static reactive power compensator（static var compensator,SVC）voltage,the Gravitational search algorithm（GSA）is applied to improve SVC voltage of fuzzy PID control algorithm.On the basis of SVC fuzziness of input and output processing,the GSA algorithm is used to optimize fuzzy rules,proportion coefficient and quantitative factors.The experimental results show that the accuracy of GSA-PID is higher than fuzzy PID and conventional PID,and realizes the SVC optimization control.

关 键 词：引力搜索算法 静止无功补偿器 模糊规则 PID控制 隶属度函数 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]