Aimed at the problem that the Hammerstein models and their improved ones reported until now can only provide limited identification accuracy when applied in the two-input single-output ( TISO) systems, a normalized TISO nonlinear Hammerstein model identification method was proposed and was applied in the nonlinear identification of supercharged boiler combustion process. Nonlinear elements which influence the combustion have different nonlinear hardness at different loads, which make it impossible to acquire an excellent accuracy in the whole range of loads when using only a set of nonlinear parameters for general TISO Hammerstein model. For this reason, the normalized TISO Hammerstein system model was introduced. The results indicate that the proposed method can describe the influence of the two inputs on a system output accurately, which in turns greatly improves the identification accuracy. Also, ideal identification accuracy can be obtained with only one set of locally optimized parameters in a multi-load area, which proves the validity of the proposed method.%针对现有Hammerstein模型及其改进模型对双输入单输出系统只能提供有限辨识精度的问题,提出一种归一化的双输入单输出(two-input single-output,TISO)Hammerstein系统模型辨识方法,并将其应用于增压锅炉燃烧辨识.在不同的负荷区域内,影响锅炉燃烧的非线性因素具有不同的非线性强度,对于常规TISO Hammerstein辨识模型,使用一组非线性辨识参数无法在多负荷范围内获得较高的辨识精度,因此提出归一化的TISO Hammerstein辨识模型.辨识结果表明,归一化TISO非线性Hammerstein模型辨识方法能够准确描述两输入变量对系统输出产生的影响,大大提高了辨识精度.并且选取一组局部最佳参数进行辨识就可以在多负荷区域内得到较好的辨识精度,证明了所提方法的有效性.
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