控制理论(社会学)
非线性系统
机械系统
有界函数
集合(抽象数据类型)
国家(计算机科学)
计算机科学
控制器(灌溉)
过程(计算)
理论(学习稳定性)
引力奇点
混合动力系统
数学优化
数学
控制工程
控制系统
控制(管理)
随机过程
非线性控制
电流(流体)
工程类
作者
Junsheng Zhao,Lifang Qiu,Zong-Yao Sun,Huaicheng Yan,Weihai Zhang
标识
DOI:10.1109/tsmc.2025.3647491
摘要
This article explores a new strategy for designated time stabilization of stochastic time-varying nonlinear systems. Conventional prescribed-time stabilization has limitations in practical engineering due to singularities induced by infinite control amplitude and a lack of manipulation of the state response after a prescribed time. To address these challenges, we build a hybrid stabilization controller using state-scale techniques and a finite-time stabilization process that is bounded in probability over the full range, guaranteeing that the closed-loop system has a solution that is almost surely unique at a designated time. Compared to the current prescribed stabilization results, the proposed strategy not only ensures that the state of the system converges in probability to a compact set at a designated time and belongs to the set after which it eventually enjoys fast finite-time convergence. Finally, the effectiveness of the strategy is verified by simulating a real mass-spring mechanical system.
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