Finite‐time state‐feedback stabilization of high‐order stochastic nonlinear systems with an asymmetric output constraint

Abstract

This article focuses on finite-time state-feedback stabilization for high-order stochastic nonlinear systems with an asymmetric output constraint. In the presence of the systems with uncertain control coefficients, a novel asymmetric barrier Lyapunov function is constructed to manipulate the output constraint for the systems. By adding a power integrator technique and sign function, this article designs a state-feedback controller by recursive method for the high-order stochastic nonlinear systems. While guaranteeing output constraint, the finite-time state-feedback stabilization is achieved for the proposed stochastic nonlinear systems. It is shown that the control problem under consideration is solvable. Finally, the efficiency of the control strategy is illustrated by a simulation example. K E Y W O R D Sadding a power integrator technique, asymmetric output constraint, high-order stochastic nonlinear systems

Adaptive output feedback asymptotic tracking for uncertain nonlinear systems with dead-zone input

“…With the continuous improvement of system performance requirements in modern industry, the nonlinear systems have received extensive attention (Batista et al, 2022; Gao et al, 2022; Liu et al, 2022a; Lu and Li, 2021; Wang et al, 2020; Xu et al, 2022). Many important control methods have been proposed to investigate nonlinear systems.…”

Fast finite‐time adaptive tracking control for non‐strict feedback stochastic nonlinear systems with full state constraints

“…Subsequently, the study of FTS was extended to linear and nonlinear systems 3‐8 . In addition, finite‐time control strategies are naturally introduced to stochastic nonlinear systems based on stability criteria and backstepping techniques 9,10 . However, the rate of convergence is faster for exponential stabilization than for FTS when the initial state is far from the origin.…”

“…The contributions of this article are summarized as follows:This article investigates the problem of adaptive fast finite‐time tracking control for uncertain stochastic nonlinear systems with full‐state constraints. Compared with the finite‐time control of References 1‐10, the control strategy in this article accelerates the convergence speed by adjusting the controller parameters and reduces the requirement of initial conditions, which provides a new idea for dealing with more general fast finite‐time tracking control problems for stochastic nonlinear systems with parameter uncertainty. Compared with the fast finite‐time control methods of References 10‐14, this article takes full‐state constraints into accounting for stochastic nonlinear systems for the first time, which not only ensures the fast convergence performance of the output but also keeps the state constrained within a specific range. …”

“…[3][4][5][6][7][8] In addition, finite-time control strategies are naturally introduced to stochastic nonlinear systems based on stability criteria and backstepping techniques. 9,10 However, the rate of convergence is faster for exponential stabilization than for FTS when the initial state is far from the origin. To address this problem, a fast finite-time control strategy has been proposed, [11][12][13][14] which improves the rapidity and robustness of convergence.…”

Adaptive event‐triggered tracking control for a class of stochastic nonlinear systems with full‐state constraints

“…Many studies have been invested in this area recently. For examples, Jiang et al [15] discussed the stabilization problem for the sector-bounded stochastic nonlinear systems; Gao et al [16] focused on finite-time state-feedback stabilization for high-order stochastic nonlinear systems with an asymmetric output constraint; for the stochastic nonlinear systems that may suffer from uncertainties such as parametric uncertainties, time-varying delay, unknown powers, and stochastic inverse dynamics, Wang et al [17] proposed an adaptive state-feedback stabilization scheme. It should be pointed out that all the control strategies mentioned above are based on continuous control.…”