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

Authors:
Publisher website
Google Scholar
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.
Funding Information
  • National Natural Science Foundation of China (61903098, 61973131, 61733009)
  • Natural Science Foundation of Heilongjiang Province of China (LH2020F024)
  • Fujian Outstanding Youth Science Fund (2020J06022)
  • National Research Foundation of Korea
  • Korea government (NRF-2020R1A2C1005449)
  • Fundamental Research Funds for the Central Universities (3072021CFT0403)
  • China Postdoctoral Science Foundation (2019M661255, 2021T140149)
  • Postdoctoral Science Foundation of Heilongjiang Province (LBH-Z19133)
  • Key-Area Research and Development Program of Guangdong Province (2020B0909020001)
  • Scientific Research Funds of Huaqiao University (605-50Y19010)

This publication has 43 references indexed in Scilit: