Stabilization of Triangular Nonlinear Systems With Multiplicative Stochastic State Sensing Noise

• 成果类型: Article
• 署名作者: Li, Wuquan; Krstic, Miroslav
• 署名单位: Ludong University; University of California System; University of California San Diego
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3201032
• 发表日期: 2023
• 页码: 3798-3805
• 关键词: Nonlinear systems; uncertainty; Robot sensing systems; Stochastic processes; control design; Closed loop systems; Lyapunov methods; Multiplicative; Nonlinear systems; stochastic sensor uncertainty

摘要

We present new state feedback control designs for lower/upper triangular nonlinear systems with multiplicative stochastic sensor uncertainty. For lower triangular nonlinear systems with small sensor noise, we develop a novel control design where the control gains are suitably constructed to simultaneously dominate the nonlinear functions and sensor noise of sufficiently small multiplicative gain. For upper triangular nonlinear systems, we propose a new low-gain domination design, the advantage of which is that it can effectively deal with the sensor noise with arbitrarily large intensities. These two designs can both ensure that the closed-loop system has an almost surely unique global solution; the origin of the closed-loop system is mean-square stable, and the states can be regulated to zero almost surely. Finally, two simulation examples are given to illustrate the designs.