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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。
Abstract：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.
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基本信息:
中图分类号:TM761.1;TP18
引用信息:
[1]谭广通.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[J].微型电脑应用,2018,34(04):30-32+49.
2018-04-20
2018-04-20