Switch detection and robust parameter estimation for slowly switched Hammerstein systems

被引：8
作者：
Wang, Zhu [1 ]
An, Haoran [1 ]
Luo, Xionglin [1 ]
机构：
[1] China Univ Petr, Dept Automat, Beijing 102249, Peoples R China
来源：
NONLINEAR ANALYSIS-HYBRID SYSTEMS | 2019年 / 32卷
基金：
中国国家自然科学基金;
关键词：
Hammerstein system; Slowly switched system; Impulsive noise; Switch detection; Robust estimation; LEAST-SQUARES IDENTIFICATION; MARKOVIAN JUMP SYSTEMS; RECURSIVE-IDENTIFICATION; NONLINEAR-SYSTEMS; ALGORITHM;
D O I：
10.1016/j.nahs.2018.12.002
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Switch detection and robust identification for slowly switched Hammerstein systems are considered in this paper. The switching law is slow, arbitrary and cannot be observed online. A two-identifier-based switch detection scheme is proposed, in order to achieve fast adaptability and robustness of parameter estimation. Specifically, at first, a recursive identification method based on long-horizon iteration is exploited under impulsive noise, and its convergence for time-invariant systems is verified. Secondly, to follow the changes of real processes, a forgetting factor is introduced, and two recursive identifiers with different horizon lengths are developed. Identifier (I) with the long horizon length can resist the influence of outliers, and Identifier (II) is responsible for process rapid reactions. Then, the estimated difference between two identifiers is analyzed to distinguish possible switching points from impulsive noise. Consequently, the two-identifier-based switch detection scheme is formed. Finally, a simulation example demonstrates the effectiveness of the proposed scheme. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码：202 / 213
页数：12
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