Work

Adaptive state-feedback control for low-order stochastic nonlinear systems with an output constraint and SiISS inverse dynamics

Year: 2025

Type: article

Abstract: This paper focuses on state-feedback adaptive control for stochastic low-order nonlinear systems with an output constraint and stochastic integral input-to-state stability (SiISS) inverse dynamics. The system with an output constraint was transformed straightforwardly into the equivalent system without a constraint using important coordinate transformations. SiISS was used to characterize unmeasured stochastic inverse dynamics. By introducing Lyapunov functions and using the stochastic systems stability theorem, we constructed a new adaptive state-feedback controller that assures the closed-loop system's trivial solution is stable in probability while fulfilling the requirements of the output constraint and all closed-loop signals are likely to be almost surely bounded. The validity of the control scheme presented in this paper was demonstrated by using simulation outcomes.

Source: AIMS Mathematics

DOI: 10.3934/math.2025508

Authors: Mengmeng Jiang, Qiqi Ni

Institution: Liaocheng University

Language: English

Topic: Adaptive Control of Nonlinear Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funder: National Natural Science Foundation of China