Saved in:
Bibliographic Details
Main Authors: Kong, Chuiliu, Wang, Ying
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2404.16282
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910426202112000
author Kong, Chuiliu
Wang, Ying
author_facet Kong, Chuiliu
Wang, Ying
contents This paper considers an adaptive tracking control problem for stochastic regression systems with multi-threshold quantized observations. Different from the existing studies for periodic reference signals, the reference signal in this paper is non-periodic. Its main difficulty is how to ensure that the designed controller satisfies the uniformly bounded and excitation conditions that guarantee the convergence of the estimation in the controller under non-periodic signal conditions. This paper designs two backward-shifted polynomials with time-varying parameters and a special projection structure, which break through periodic limitations and establish the convergence and tracking properties. To be specific, the adaptive tracking control law can achieve asymptotically optimal tracking for the non-periodic reference signal; Besides, the proposed estimation algorithm is proved to converge to the true values in almost sure and mean square sense, and the convergence speed can reach $O\left(\frac{1}{k}\right)$ under suitable conditions. Finally, the effectiveness of the proposed adaptive tracking control scheme is verified through a simulation.
format Preprint
id arxiv_https___arxiv_org_abs_2404_16282
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Adaptive tracking control for non-periodic reference signals under quantized observations
Kong, Chuiliu
Wang, Ying
Systems and Control
This paper considers an adaptive tracking control problem for stochastic regression systems with multi-threshold quantized observations. Different from the existing studies for periodic reference signals, the reference signal in this paper is non-periodic. Its main difficulty is how to ensure that the designed controller satisfies the uniformly bounded and excitation conditions that guarantee the convergence of the estimation in the controller under non-periodic signal conditions. This paper designs two backward-shifted polynomials with time-varying parameters and a special projection structure, which break through periodic limitations and establish the convergence and tracking properties. To be specific, the adaptive tracking control law can achieve asymptotically optimal tracking for the non-periodic reference signal; Besides, the proposed estimation algorithm is proved to converge to the true values in almost sure and mean square sense, and the convergence speed can reach $O\left(\frac{1}{k}\right)$ under suitable conditions. Finally, the effectiveness of the proposed adaptive tracking control scheme is verified through a simulation.
title Adaptive tracking control for non-periodic reference signals under quantized observations
topic Systems and Control
url https://arxiv.org/abs/2404.16282