基于RLS的汽轮机数字电液调节系统参数辨识

采用递推最小二乘法（RLS）进行汽轮机数字电液调节系统的参数辨识，通过双线性变换法将连续模型转化为离散模型，推导了电液转换器和油动机环节的辨识模型.为剔除辨识数据中环节通带外信号的不利影响，采用Butterworth低通滤波器进行滤波处理，根据环节对象的预计通带，设计低通滤波器的通带截止频率和阻带截止频率，有效提高了参数的辨识精度.以某300 MW机组数字电液 (DEH) 调节系统为研究对象，应用传递函数法建立DEH模型结构图，经该机组负荷扰动实测试验数据的计算验证表明，递推最小二乘法具有辨识速度快、建模效率高特点，适合于复杂的现场对象参数辨识.

Recursive least square method based parameter identification of steam turbine digital electric-hydraulic governing system

The recursive least square(RLS) method was employed to identify the parameter.The discrete model was established by employing the dual linear transformation,and the identification models of electric-hydraulic converter and servomotor module were derived.Butterworth low-pass filter was applied to avoid the disadvantage of off-band signal and improve the identification precision.The cut-off frequency of Butterworth low-pass filter was designed according to the forecasting band of the object segment.The transfer function method was used to establish the model of digital electric-hydraulic(DEH) governing system of a 300 MW unit.The disturbed test data of the unit show that the RLS method has a high speed and it is efficient for parameter identification of complicated objects.