Adaptive State-Feedback Stabilization of Stochastic High-Order Nonlinear Systems With Time-Varying Powers and Stochastic Inverse Dynamics

被引:27
|
作者
Li, Guang-Ju [1 ]
Xie, Xue-Jun [2 ]
机构
[1] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
[2] Qufu Normal Univ, Inst Automat, Jining 273165, Peoples R China
基金
中国国家自然科学基金;
关键词
Springs; Time-varying systems; Adaptive systems; Stochastic systems; Nonlinear dynamical systems; Lyapunov methods; State-feedback stabilization; stochastic high-order nonlinear systems; stochastic inverse dynamics; time-varying powers;
D O I
10.1109/TAC.2020.2969547
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article investigates adaptive state-feedback stabilization problem for a class of stochastic high-order nonlinear systems with unknown time-varying powers and stochastic inverse dynamics for the first time. The existence of stochastic inverse dynamics, unknown parameters, and time-varying powers makes stochastic high-order nonlinear systems essentially different from the related papers, which brings a series of obstacles to achieve the control objective. By virtue of the parameter separation principle, adaptive technique and some flexible algebraic methods, a novel adaptive state-feedback controller is designed to guarantee that the equilibrium of the closed-loop system is globally stable in probability. Finally, a simulation is provided to demonstrate the effectiveness of the control scheme.
引用
收藏
页码:5360 / 5367
页数:8
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