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中文摘要：
针对多输入多输出线性时变系统参数模型的辨识问题,利用块-脉冲函数展开式和块-脉冲函数独特的脱关性和互换性等性质,采用一种新型的二值正交函数BPF,利用系统的状态方程,推导出简易线性时变系统的系统矩阵和输入矩阵的分段恒定矩阵的参数模型辨识算法。该辨识算法不受预先选定的时间分段数的限制,辨识可延续到任意需要时刻;当分段步长趋近于零时,各分段子区间的误差趋近于零,且由于误差在各个区间之间不传递,故该算法是稳定和收敛的。仿真实例验证了辨识算法的有效性。
英文摘要：
By adopting a new block-pulse function （BPF） and applying the expanding expressions and distinctive characters of BPF, such as properties of breaking off relation and exchangeability, a parametric model identification algorithm of piece-wise constant matrices in multi-input and multi-output （MIMO） linear time-varying system was derived. The identification process can continue for any necessary time and is not constrained by pre-selected number of time piece-wise sections. As piece-wise step length approaches to zero, the error in each piece-wise interval approaches to zero. Because the errors in individual intervals do not transfer each other, the algorithm is stable and convergent. Simulation example verifies the effectiveness of the proposed algorithm.
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