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Recursive identification for Hammerstein-Wiener systems with dead-zone input nonlinearity

机译:具有死区输入非线性的Hammerstein-Wiener系统的递归辨识

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摘要

A new recursive algorithm is proposed for the identification of a special form of Hammerstein-Wiener system with dead-zone nonlinearity input block. The direct motivation of this work is to implement on-line control strategies on this kind of system to produce adaptive control algorithms. With the parameterization model of the Hammerstein-Wiener system, a special form of model estimation error is defined; and then its approximate formula is given for the following derivation. Based on these, a recursive identification algorithm is established that aims at minimizing the sum of the squared parameter estimation errors. The conditions of uniform convergence are obtained from the property analysis of the proposed algorithm and an adaptive setting method for a weighted factor in the algorithm is given, which enhances the convergence of the proposed algorithm. This algorithm can also be used for the identification of the Hammerstein systems with dead-zone nonlinearity input block. Three simulation examples show the validity of this algorithm.
机译:提出了一种新的递归算法,用于识别带有死区非线性输入块的特殊形式的Hammerstein-Wiener系统。这项工作的直接动机是在这种系统上实施在线控制策略,以产生自适应控制算法。利用Hammerstein-Wiener系统的参数化模型,定义了一种特殊形式的模型估计误差;然后给出其近似公式用于以下推导。基于这些,建立了一种递归识别算法,旨在最小化平方参数估计误差之和。通过对所提算法的性能分析,得出了均匀收敛的条件,给出了算法中加权因子的自适应设置方法,提高了所提算法的收敛性。该算法也可用于识别具有死区非线性输入块的Hammerstein系统。三个仿真实例证明了该算法的有效性。

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