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

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) switchi...

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Vydáno v:IEEE transaction on neural networks and learning systems Ročník 34; číslo 9; s. 5897 - 5910
Hlavní autoři: Chen, Liheng, Zhu, Yanzheng, Ahn, Choon Ki
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.09.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Actuator degradation
Actuators
adaptive neural network (NN) observer
Artificial neural networks
Degradation
Design
Dwell time
Neural networks
Observers
persistent dwell time
Quantization (signal)
signal quantization
Switched systems
Switches
Switching
ISSN:2162-237X, 2162-2388, 2162-2388
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Shrnutí: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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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2021.3131412