在风电系统中RBFNN自适应输出反馈控制策略

提出了一种基于RBFNN自适应输出反馈控制器，针对平均风速下不同的线性数学模型，采用区域极点配置的方法设计输出反馈控制器的反馈增益，然后由RBF神经网络对不同风速下的稳态工作点和输出反馈增益之间的非线性映射关系进行逼近.这种控制器可根据风速的变化，给出相应的输出反馈增益G，使得风电系统能够以满意的阻尼比，无静态误差地跟踪不同的期望工作点，同时对频繁出现的阵风扰动具有一定的抑制作用.并通过仿真对这一控制器的良好性能进行了验证.

Research on RBFNN adaptive output feedback control strategy in WECS

An adaptive output feedback control strategy based on RBF neural network(RBFNN) is presented.For the linearized mathematical models at the different wind velocity,the feedback gains of output feedback controllers were designed based on pole assignment in a vertical strip.The nonlinear mapping relationship between steady operation points and output feedback gains was approximated Afterwards by RBF neural network.The wind electricity conversion system(WECS) can operate on the expected points with zero-tracking-error and suitable damp ratio in a wide range of wind velocities,and effectively restrains the continually disturbance of gust.The dynamic performances of the proposed controller has been verified by MATLAB/Simulink simulation.