【摘要】 针对超超临界机组过热蒸汽系统模型辨识,采用基于数据驱动的闭环子空间辨识方法直接得到系统的阶跃响应系数,结合传统的SISO(Single Input Single Output)辨识方法,并利用最小二乘算法回归出系统的低阶传递函数模型.通过对某电厂超超临界机组过热蒸汽系统进行闭环辨识,结果表明,该策略很好地融合了子空间方法的简便性以及传统SISO辨识方法的最优性,并成功用于超超临界机组过热蒸汽系统模型辨识.更多还原

【Abstract】 The superheated steam system ultra-supercritical unit is a multi-input and multi-output system.In this paper,a data-driven subspace approach is introduced for the model identification of the superheated steam system.In the approach,the unit step response coefficients are drawn directly,then the low-order transfer function of the system is obtained by least-square regression.Finally,closed loop identification based on data-driven subspace approach is applied to the superheated steam system of ultra-supercritical coal-fired power unit.Real application shows that proposed identification strategy has a small computational cost and can meet the accuracy requirements in industrial sites.更多还原