Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements

Liheng Chen; Yanzheng Zhu; Choon Ki Ahn

doi:10.1109/TNNLS.2021.3131412

Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements

Liheng Chen, Yanzheng Zhu, Choon Ki Ahn

Research output: Contribution to journal › Article › peer-review

55 Citations (Scopus)

Abstract

This study is concerned with the adaptive neural network (NN) observer design problem for continuous-time switched systems via quantized output signals. A novel NN observer is presented in which the adaptive laws are constructed using quantized measurements. Then, persistent dwell time (PDT) switching is considered in the observer design to describe fast and slow switching in a unified framework. Accurate estimations of state and actuator efficiency factor can be obtained by the proposed observer technique despite actuator degradation. Finally, a simulation example is provided to illustrate the effectiveness of the developed NN observer design approach.

Original language	English
Pages (from-to)	5897-5910
Number of pages	14
Journal	IEEE Transactions on Neural Networks and Learning Systems
Volume	34
Issue number	9
DOIs	https://doi.org/10.1109/TNNLS.2021.3131412
Publication status	Published - 2023 Sept 1

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

Actuator degradation
adaptive neural network (NN) observer
persistent dwell time
signal quantization
switched systems

ASJC Scopus subject areas

Software
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications

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10.1109/TNNLS.2021.3131412

Cite this

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abstract = "This study is concerned with the adaptive neural network (NN) observer design problem for continuous-time switched systems via quantized output signals. A novel NN observer is presented in which the adaptive laws are constructed using quantized measurements. Then, persistent dwell time (PDT) switching is considered in the observer design to describe fast and slow switching in a unified framework. Accurate estimations of state and actuator efficiency factor can be obtained by the proposed observer technique despite actuator degradation. Finally, a simulation example is provided to illustrate the effectiveness of the developed NN observer design approach.",

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AB - This study is concerned with the adaptive neural network (NN) observer design problem for continuous-time switched systems via quantized output signals. A novel NN observer is presented in which the adaptive laws are constructed using quantized measurements. Then, persistent dwell time (PDT) switching is considered in the observer design to describe fast and slow switching in a unified framework. Accurate estimations of state and actuator efficiency factor can be obtained by the proposed observer technique despite actuator degradation. Finally, a simulation example is provided to illustrate the effectiveness of the developed NN observer design approach.

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JO - IEEE Transactions on Neural Networks and Learning Systems

JF - IEEE Transactions on Neural Networks and Learning Systems

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Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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