摘要
热工过程往往表现出非线性、大迟延和大惯性等特点,难以建立精确的数学模型。针对这一问题,应用LMS自适应滤波器对火电厂过热汽温对象进行建模。该方法以过热器的入口和出口汽温作为滤波器的激励信号和期望信号,根据最小梯度算法调整滤波器抽头权值,获得过热汽温的FIR模型。文中建模方法计算复杂度低,仿真结果和某电厂运行数据验证了这种方法的有效性。
The thermal process shows the feature of non-linearity, great delay, big inertia, so it is difficult to buihl the mathematical model for it. To solve this problem, the LMS （Least-mean-square） adaptive filter is introduced for the modelling of the superheated steam temperature. Takes the input and output of the superheater as the inspire signal and the destination signal of the filter, the LMS filter adjusts the tap weights based on least gradient algorithm, then gets a FIR model for the superheated steam process. The modelling method used in the paper has low complexity. The simulation result and power plant operating data demonstrate the effectiveness of the modelling method.
出处
《陕西电力》
2010年第4期22-25,共4页
Shanxi Electric Power
关键词
LMS算法
建模
自适应滤波器
过热器
least mean square algorithm
modelling
adaptive filter
superheater
