Finite-Time Control for Stochastic Systems with Input and Measurement Powers of Unknown Time-Varying Function Forms

This article addresses the finite-time tracking control of stochastic systems with time-varying input and measurement powers. Compared to the existing results with known input powers, the input powers of the system studied in this paper are unknown time-varying functions, which makes the design of control strategy extremely difficult. Additionally, since the signals will deviate during actual measurements, this article also considers the problem of measurement power drifts. To resolve these two problems, this article constructs a new controller by establishing new error variables, which guarantees the finite-time stability of the stochastic system. Finally, the efficiency of the proposed control strategy is confirmed by simulation experiments.

Authors

Institutions

Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/rcae62637.2024.10834155
Primary Topic
Stability and Control of Uncertain Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Finite-Time Control for Stochastic Systems with Input and Measurement Powers of Unknown Time-Varying Function Forms

Qikun Shen, Yadong Yang
Stability and Control of Uncertain Systems
article

Finite-Time Control for Stochastic Systems with Input and Measurement Powers of Unknown Time-Varying Function Forms

Qikun Shen, Yadong Yang
article en

Abstract

This article addresses the finite-time tracking control of stochastic systems with time-varying input and measurement powers. Compared to the existing results with known input powers, the input powers of the system studied in this paper are unknown time-varying functions, which makes the design of control strategy extremely difficult. Additionally, since the signals will deviate during actual measurements, this article also considers the problem of measurement power drifts. To resolve these two problems, this article constructs a new controller by establishing new error variables, which guarantees the finite-time stability of the stochastic system. Finally, the efficiency of the proposed control strategy is confirmed by simulation experiments.

Yangzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 69%
Stability and Control of Uncertain Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.