基于RBF模糊神经网络的垂直轴风力机设计  

Research on Vertical Axis Wind Turbine Control Algorithm Based on RBF Fuzzy Neural Network

作　　者：张谦[1] 王双红[1] 陈海峰[1] 

机构地区：[1]中原工学院电子信息学院,郑州450007

出　　处：《计算机测量与控制》2014年第7期2237-2239,2243,共4页Computer Measurement &Control

摘　　要：半转结构垂直轴风力机具有优良的空气动力特性,为了进一步提高风电系统输出电能的质量,在RBF神经网络与模糊逻辑系统的函数等价条件下,探索了基于T-S模糊模型的RBF模糊神经网络控制算法,并依此设计出两叶结构半转式垂直轴风力机控制器;通过与常规PID控制算法的仿真比较,表明基于T-S模型的RBF模糊神经网络控制算法在两叶结构半转式垂直轴风力机的恒转速控制方面具有一定的优越性。Seimi-rotary VAWT （vertical axis wind turbine） has excellent aerodynamic properties. In order to improve the quality of electricity produced by wind turbine,, the RBF fuzzy neural network was studied on the condition that the RBF neural network was equal to the function of fuzzy logic system and, twp-leaf semi-rotary VAWT controller was based on this algorithm. Compared with the conventional PID control algorithm, the simulation result shows that the RBF fuzzy neural network control algorithm based on T-S model has some superiority in the application of two-leaf semi-rotary VAWT constant revolution control.

关 键 词：垂直轴风力机 T—S模糊模型 RBF模糊神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]