Adaptive Observers for a Class of State-Affine Output-Injection Nonlinear Systems with Sampled Measurements

被引：0
|
作者：
Xie, Chun-Hua [1 ,2 ]
Yang, Hui [1 ,2 ]
Li, Zhe [3 ]
机构：
[1] East China Jiaotong Univ, Sch Elect & Automat Engn, Nanchang 330013, Jiangxi, Peoples R China
[2] Key Lab Adv Control & Optimizat Jiangxi Prov, Nanchang 330013, Jiangxi, Peoples R China
[3] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
来源：
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
Adaptive Observer; Sampled Measurements; Output-injection Nonlinear Systems; State and Unknown Parameter Estimation;
D O I：
10.1109/ccdc.2019.8832377
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper investigates the problem of simultaneous estimation of the states and unknown parameters for multiple-input multiple-output (MIMO) output-injection nonlinear systems with sampled measurements, where the output equation involves linear parametrization. A continuous-discrete adaptive observer is proposed and shown to be exponentially convergent, provided that: 1) the sampling period is small; and 2) a well-defined persistent excitation condition holds. In particular, the existing results are focused on the systems, where the output equation does not involve unknown parameters. Finally, the proposed approach is supported by simulation results.
引用
收藏
页码：5372 / 5379
页数：8
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