A recursive identification method for continuous time-varying linear systems

Z. Jiang, W. Schaufelberger
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引用次数: 4

Abstract

A method for online identification of continuous time-varying linear systems is proposed based on the block pulse functions. From the relations between entries of the block pulse operational matrices, simple regression equations corresponding to the original differential equation models with time-varying parameters can be obtained, and algorithms developed in discrete-time model identification can be applied directly to estimate the time-varying parameters of the continuous models without much modification. Compared with other methods for solving the same identification problem, no analog devices, no large computations in the data preparation stage, and no initial values are involved in this new method. Therefore, the estimation procedure is much simpler. Owing to the block pulse regression equations, the proposed recursive method is suitable for online identification of continuous time-varying linear systems from their sampled input and output data by means of digital computers.<>
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连续时变线性系统的递归辨识方法
提出了一种基于块脉冲函数的连续时变线性系统在线辨识方法。根据块脉冲运算矩阵各项之间的关系,可以得到与原始时变参数微分方程模型相对应的简单回归方程,并且可以直接应用离散时间模型辨识中开发的算法来估计连续模型的时变参数,而无需进行大量修改。与解决相同识别问题的其他方法相比,该方法不需要模拟设备,不需要数据准备阶段的大量计算,也不需要初始值。因此,估计过程要简单得多。由于采用了块脉冲回归方程,所提出的递归方法适用于用数字计算机对连续时变线性系统的输入输出采样数据进行在线辨识。
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