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

18 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
Journal	IEEE Transactions on Neural Networks and Learning Systems
DOIs	https://doi.org/10.1109/TNNLS.2021.3131412
Publication status	Accepted/In press - 2021

Keywords

Actuator degradation
Actuators
Artificial neural networks
Degradation
Observers
Quantization (signal)
Switched systems
Switches
adaptive neural network (NN) observer
persistent dwell time
signal quantization
switched systems.

ASJC Scopus subject areas

Software
Computer Science Applications
Computer Networks and Communications
Artificial Intelligence

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10.1109/TNNLS.2021.3131412

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title = "Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements",

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.",

keywords = "Actuator degradation, Actuators, Artificial neural networks, Degradation, Observers, Quantization (signal), Switched systems, Switches, adaptive neural network (NN) observer, persistent dwell time, signal quantization, switched systems.",

author = "Liheng Chen and Yanzheng Zhu and Ahn, {Choon Ki}",

note = "Publisher Copyright: IEEE",

year = "2021",

doi = "10.1109/TNNLS.2021.3131412",

language = "English",

journal = "IEEE Transactions on Neural Networks and Learning Systems",

issn = "2162-237X",

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TY - JOUR

T1 - Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements

AU - Chen, Liheng

AU - Zhu, Yanzheng

AU - Ahn, Choon Ki

N1 - Publisher Copyright: IEEE

PY - 2021

Y1 - 2021

N2 - 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.

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.

KW - Actuator degradation

KW - Actuators

KW - Artificial neural networks

KW - Degradation

KW - Observers

KW - Quantization (signal)

KW - Switched systems

KW - Switches

KW - adaptive neural network (NN) observer

KW - persistent dwell time

KW - signal quantization

KW - switched systems.

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U2 - 10.1109/TNNLS.2021.3131412

DO - 10.1109/TNNLS.2021.3131412

M3 - Article

AN - SCOPUS:85121378838

SN - 2162-237X

JO - IEEE Transactions on Neural Networks and Learning Systems

JF - IEEE Transactions on Neural Networks and Learning Systems

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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