This paper addresses distributed parameter estimation in stochastic dynamic systems with quantized measurements, constrained by quantized communication and Markovian switching directed topologies. To enable accurate recovery of the original signal from quantized communication signal, a persistent excitation-compliant linear compression encoding method is introduced. Leveraging this encoding, this paper proposes an estimation-fusion type quantized distributed identification algorithm under a stochastic approximation framework. The algorithm operates in two phases: first, it estimates neighboring estimates using quantized communication information, then it creates a fusion estimate by combining these estimates through a consensus-based distributed stochastic approximation approach. To tackle the difficulty caused by the coupling between these two estimates, two combined Lyapunov functions are constructed to analyze the convergence performance. Specifically, the mean-square convergence of the estimates is established under a conditional expectation-type cooperative excitation condition and the union topology containing a spanning tree. Besides, the convergence rate is derived to match the step size's order under suitable step-size coefficients. Furthermore, the impact of communication uncertainties including stochastic communication noise and Markov-switching rate is analyzed on the convergence rate. A numerical example illustrates the theoretical findings and highlights the joint effect of sensors under quantized communication. (c) 2025 Published by Elsevier Ltd.

Publication:

AUTOMATICA

http://dx.doi.org/10.1016/j.automatica.2025.112658

Author:

Ying Wang

State Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China

Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm 11428, Sweden

E-mail addresses: wangying96@amss.ac.cn

Yanlong Zhao

State Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China

School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China

Corresponding author at: State Key Laboratory of Mathematical Sci-ences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China.

E-mail addresses: ylzhao@amss.ac.cn

Ji-Feng Zhang e,a,d

a State Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China

d School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China

e School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou 450007, PR China

E-mail addresses: jif@iss.ac.cn